Search results for: medical imaging

Authors: Rishav Shrestha, Yong Zhang

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The Anti-Stoke upconversion process has been used extensively for bioimaging and is recently being used for photoactivated therapy in cancer utilizing upconversion nanoparticles (UCNs). The UCNs have an excitation band at 980nm; 980nm laser excitation used to produce UV/Visible emissions also produce a heating effect. Light-to-heat conversion has been observed in nanoparticles(NPs) doped with neodymium(Nd) or ytterbium(Yb)/erbium(Er) ions. Despite laser-induced heating in Rare-earth doped NPs being proven to be a relatively efficient process, only few attempts to use them as photothermal agents in biosystems have been made up to now. Gold nanoparticles and carbon nanotubes are the most researched and developed for photothermal applications. Both have large heating efficiency and outstanding biocompatibility. However, they show weak fluorescence which makes them harder to track in vivo. In that regard, UCNs are attractive due to their excellent optical features in addition to their light-to-heat conversion and excitation by NIR, for imaging and spatiotemporally releasing drugs. In this work, we have utilized a simple method to coat Nd doped UCNs with thermoresponsive polymer PNIPAM on which 4-Hydroxytamoxifen (4-OH-T) is loaded. Such UCNs demonstrate a high loading efficiency and low leakage of 4-OH-T. Encouragingly, the release of 4-OH-T can be modulated by varying the power and duration of the NIR. Such UCNs were then used to demonstrate imaging and controlled photothermal release of 4-OH-T in MCF-7 breast cancer cells.

Keywords: cancer therapy, controlled release, photothermal release, upconversion nanoparticles

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Authors: Yimei Huang, Harvey Lui, Jianhua Zhao, Zhenguo Wu, Haishan Zeng

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Conventional laser treatment of skin diseases and cosmetic surgery is based on the principle of one-photon absorption selective photothermolysis which relies strongly on the difference in the light absorption between the therapeutic target and its surrounding tissue. However, when the difference in one-photon absorption is not sufficient, collateral damage would occur due to indiscriminate and nonspecific tissue heating. To overcome this problem, we developed a spatially selective photothermolysis method based on multiphoton absorption in which the heat generation is restricted to the focal point of a tightly focused near-infrared femtosecond laser beam aligned with the target of interest. A multimodal optical microscope with co-registered reflectance confocal imaging (RCM), two-photon fluorescence imaging (TPF), and second harmonic generation imaging (SHG) capabilities was used to perform and monitor the spatially selective photothermolysis. Skin samples excised from the shaved backs of euthanized NODSCID mice were used in this study. Treatments were performed by focusing and scaning the laser beam in the dermis with a 50µm×50µm target area. Treatment power levels of 200 mW to 400 mW and modulated pulse trains of different duration and period were experimented. Different treatment parameters achieved different degrees of spatial confinement of tissue alterations as visualized by 3-D RCM/TPF/SHG imaging. At 200 mW power level, 0.1 s pulse train duration, 4.1 s pulse train period, the tissue damage was found to be restricted precisely to the 50µm×50µm×10µm volume, where the laser focus spot had scanned through. The overlying epidermis/dermis tissue and the underneath dermis tissue were intact although there was light passing through these regions.

Keywords: multiphoton absorption photothermolysis, reflectance confocal microscopy, second harmonic generation microscopy, spatially selective photothermolysis, two-photon fluorescence microscopy

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Authors: Eashwar V. Somasundaram, Raoul R. Wadhwa, Jacob G. Scott

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The use of radiomics in measuring geometric properties of tumor images such as size, surface area, and volume has been invaluable in assessing cancer diagnosis, treatment, and prognosis. In addition to analyzing geometric properties, radiomics would benefit from measuring topological properties using persistent homology. Intuitively, features uncovered by persistent homology may correlate to tumor structural features. One example is necrotic cavities (corresponding to 2D topological features), which are markers of very aggressive tumors. We develop a data pipeline in R that clusters tumors images based on persistent homology is used to identify meaningful clinical distinctions between tumors and possibly new relationships not captured by established clinical categorizations. A preliminary analysis was performed on 16 Magnetic Resonance Imaging (MRI) breast tissue segments downloaded from the 'Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis' (I-SPY TRIAL or ISPY1) collection in The Cancer Imaging Archive. Each segment represents a patient’s breast tumor prior to treatment. The ISPY1 dataset also provided the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status data. A persistent homology matrix up to 2-dimensional features was calculated for each of the MRI segmentation. Wasserstein distances were then calculated between all pairwise tumor image persistent homology matrices to create a distance matrix for each feature dimension. Since Wasserstein distances were calculated for 0, 1, and 2-dimensional features, three hierarchal clusters were constructed. The adjusted Rand Index was used to see how well the clusters corresponded to the ER/PR/HER2 status of the tumors. Triple-negative cancers (negative status for all three receptors) significantly clustered together in the 2-dimensional features dendrogram (Adjusted Rand Index of .35, p = .031). It is known that having a triple-negative breast tumor is associated with aggressive tumor growth and poor prognosis when compared to non-triple negative breast tumors. The aggressive tumor growth associated with triple-negative tumors may have a unique structure in an MRI segmentation, which persistent homology is able to identify. This preliminary analysis shows promising results in the use of persistent homology on tumor imaging to assess the severity of breast tumors. The next step is to apply this pipeline to other tumor segment images from The Cancer Imaging Archive at different sites such as the lung, kidney, and brain. In addition, whether other clinical parameters, such as overall survival, tumor stage, and tumor genotype data are captured well in persistent homology clusters will be assessed. If analyzing tumor MRI segments using persistent homology consistently identifies clinical relationships, this could enable clinicians to use persistent homology data as a noninvasive way to inform clinical decision making in oncology.

Keywords: cancer biology, oncology, persistent homology, radiomics, topological data analysis, tumor imaging

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Authors: Sharon Yunger, Liat Altman, Yuval Garini, Yaron Shav-Tal

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Understanding the dynamics of transcription in living cells has improved since the development of quantitative fluorescence-based imaging techniques. We established a method for following transcription from a single copy gene in living cells. A gene tagged with MS2 repeats, used for mRNA tagging, in its 3' UTR was integrated into a single genomic locus. The actively transcribing gene was detected and analyzed by fluorescence in situ hybridization (FISH) and live-cell imaging. Several cell clones were created that differed in the promoter regulating the gene. Thus, comparative analysis could be obtained without the risk of different position effects at each integration site. Cells in S/G2 phases could be detected exhibiting two adjacent transcription sites on sister chromatids. A sharp reduction in the transcription levels was observed as cells progressed along the cell cycle. We hypothesized that a change in chromatin structure acts as a general mechanism during the cell cycle leading to down-regulation in the activity of some genes. We addressed this question by treating the cells with chromatin decondensing agents. Quantifying and imaging the treated cells suggests that chromatin structure plays a role both in regulating transcriptional levels along the cell cycle, as well as in limiting an active gene from reaching its maximum transcription potential at any given time. These results contribute to understanding the role of chromatin as a regulator of gene expression.

Keywords: cell cycle, living cells, nucleus, transcription

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Authors: Ananya Barui, Provas Banerjee, Jyotirmoy Chatterjee

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Application of optical technology in medicine and biology has a long track-record. In this endeavor, OCT is able to attract both engineers and biologists to work together in the field of photonics for establishing a striking non-invasive imaging technology. In contrast to other in vivo imaging modalities like Raman imaging, confocal imaging, two-photon microscopy etc. which can perform in vivo imaging upto 100-200 micron depth due to limitation in numerical aperture or scattering, however, OCT can achieve high-resolution imaging upto few millimeters of tissue structures depending on their refractive index in different anatomical location. This tomographic system depends on interference of two light waves in an interferometer to produce a depth profile of specimen. In wound healing, frequent collection of biopsies for follow-up of repair process could be avoided by such imaging technique. Real time skin OCT (the optical biopsy) has efficacy in deeper and faster illumination of cutaneou tissue to acquire high resolution cross sectional images of their internal micro-structure. Swept Source-OCT (SS-OCT), a novel imaging technique, can generate high-speed depth profile (~ 2 mm) of wound at a sweeping rate of laser with micron level resolution and optimum coherent length of 5-6 mm. Normally multi-layered skin tissue depicts different optical properties along with variation in thickness, refractive index and composition (i.e. keratine layer, water, fat etc.) according to their anatomical location. For instance, stratum corneum, the upper-most and relatively dehydrated layer of epidermis reflects more light and produces more lucid and a sharp demarcation line with rest of the hydrated epidermal region. During wound healing or regeneration, optical properties of cutaneous tissue continuously altered with maturation of wound bed. More mature and less hydrated tissue component reflects more light and becomes visible as a brighter area in comparison to immature region which content higher amount water or fat that depicts as a darker area in OCT image. Non-healing wound possess prolonged inflammation and inhibits nascent proliferative stage. Accumulation of necrotic tissues also prevents the repair of non-healing wounds. Due to high resolution and potentiality to reflect the compositional aspects of tissues in terms of their optical properties, this tomographic method may facilitate in differentiating non-healing and acute wounds in addition to clinical observations. Non-invasive OCT offers better insight regarding specific biological status of tissue in health and pathological conditions, OCT images could be associated with histo-pathological ‘gold standard’. This correlated SS-OCT and microscopic evaluation of the wound edges can provide information regarding progressive healing and maturation of the epithelial components. In the context of searching analogy between two different imaging modalities, their relative performances in imaging of healing bed were estimated for probing an alternative approach. Present study validated utility of SS-OCT in revealing micro-anatomic structure in the healing bed with newer information. Exploring precise correspondence of OCT images features with histo-chemical findings related to epithelial integrity of the regenerated tissue could have great implication. It could establish the ‘optical biopsy’ as a potent non-invasive diagnostic tool for cutaneous pathology.

Keywords: histo-pathology, non invasive imaging, OCT, wound healing

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Authors: Han Xiao

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The development of nanomedicines has recently achieved several breakthroughs in the field of cancer treatment; however, the biocompatibility and targeted burst release of these medications remain a limitation, which leads to serious side effects and significantly narrows the scope of their applications. The self-assembly of intermediate filament protein (IFP) peptides was triggered by a hydrophobic cation drug 7-amino actinomycin D (7-AAD) to synthesize pH-activatable nanoparticles (NPs) that could simultaneously locate tumors and produce antitumor effects. The designed IFP peptide included a target peptide (arginine–glycine–aspartate), a negatively charged region, and an α-helix sequence. It also possessed the ability to encapsulate 7-AAD molecules through the formation of hydrogen bonds and hydrophobic interactions by a one-step method. 7-AAD molecules with excellent near-infrared fluorescence properties could be target delivered into tumor cells by NPs and released immediately in the acidic environments of tumors and endosome/lysosomes, ultimately inducing cytotoxicity by arresting the tumor cell cycle with inserted DNA. It is noteworthy that the IFP/7-AAD NPs tail vein injection approach demonstrated not only high tumor-targeted imaging potential, but also strong antitumor therapeutic effects in vivo. The proposed strategy may be used in the delivery of cationic antitumor drugs for precise imaging and cancer therapy.

Keywords: 7-amino actinomycin D, intermediate filament protein, nanoparticle, tumor image

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Authors: Deniz Erçelen, Özlem Selcuk Bozkurt

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The course of daily human life calls for the need for memories and remembering the time and place for certain events. Recalling memories takes up a substantial amount of time for an individual. Unfortunately, scientists lack the proper technology to fully understand and observe different brain regions that interact to form or retrieve memories. The hippocampus, a complex brain structure located in the temporal lobe, plays a crucial role in memory. The hippocampus forms memories as well as allows the brain to retrieve them by ensuring that neurons fire together. This process is called “neural synchronization.” Sadly, the hippocampus is known to deteriorate often with age. Proteins and hormones, which repair and protect cells in the brain, typically decline as the age of an individual increase. With the deterioration of the hippocampus, an individual becomes more prone to memory loss. Many memory loss starts off as mild but may evolve into serious medical conditions such as dementia and Alzheimer’s disease. In their quest to fully comprehend how memories work, scientists have created many different kinds of technology that are used to examine the brain and neural pathways. For instance, Magnetic Resonance Imaging - or MRI- is used to collect detailed images of an individual's brain anatomy. In order to monitor and analyze brain functions, a different version of this machine called Functional Magnetic Resonance Imaging - or fMRI- is used. The fMRI is a neuroimaging procedure that is conducted when the target brain regions are active. It measures brain activity by detecting changes in blood flow associated with neural activity. Neurons need more oxygen when they are active. The fMRI measures the change in magnetization between blood which is oxygen-rich and oxygen-poor. This way, there is a detectable difference across brain regions, and scientists can monitor them. Electroencephalography - or EEG - is also a significant way to monitor the human brain. The EEG is more versatile and cost-efficient than an fMRI. An EEG measures electrical activity which has been generated by the numerous cortical layers of the brain. EEG allows scientists to be able to record brain processes that occur after external stimuli. EEGs have a very high temporal resolution. This quality makes it possible to measure synchronized neural activity and almost precisely track the contents of short-term memory. Science has come a long way in monitoring memories using these kinds of devices, which have resulted in the inspections of neurons and neural pathways becoming more intense and detailed.

Keywords: brain, EEG, fMRI, hippocampus, memories, neural pathways, neurons

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Authors: Sundara Subramanian Karuppasamy, Che Hua Yang

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In this work, the laser ultrasound technique has been used for analyzing and imaging the inner defects in metal blocks. To detect the defects in blocks, traditionally the researchers used piezoelectric transducers for the generation and reception of ultrasonic signals. These transducers can be configured into the sparse and phased array. But these two configurations have their drawbacks including the requirement of many transducers, time-consuming calculations, limited bandwidth, and provide confined image resolution. Here, we focus on the non-contact method for generating and receiving the ultrasound to examine the inner defects in aluminum blocks. A Q-switched pulsed laser has been used for the generation and the reception is done by using Laser Doppler Vibrometer (LDV). Based on the Doppler effect, LDV provides a rapid and high spatial resolution way for sensing ultrasonic waves. From the LDV, a series of scanning points are selected which serves as the phased array elements. The side-drilled hole of 10 mm diameter with a depth of 25 mm has been introduced and the defect is interrogated by the linear array of scanning points obtained from the LDV. With the aid of the Synthetic Aperture Focusing Technique (SAFT) algorithm, based on the time-shifting principle the inspected images are generated from the A-scan data acquired from the 1-D linear phased array elements. Thus the defect can be precisely detected with good resolution.

Keywords: laser ultrasonics, linear phased array, nondestructive testing, synthetic aperture focusing technique, ultrasonic imaging

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Authors: Dimitrios Binas, Marianna Konidari, Charis Bourgioti, Lia Angela Moulopoulou, Theodore Economopoulos, George Matsopoulos

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High grade ovarian epithelial cancer (OEC) is fatal gynecological cancer and the poor prognosis of this entity is closely related to considerable intratumoral genetic heterogeneity. By examining imaging data, it is possible to assess the heterogeneity of tumorous tissue. This study proposes a methodology for aligning, segmenting and finally visualizing information from various magnetic resonance imaging series in order to construct 3D models of heterogeneity maps from the same tumor in OEC patients. The proposed system may be used as an adjunct digital tool by health professionals for personalized medicine, as it allows for an easy visual assessment of the heterogeneity of the examined tumor.

Keywords: image segmentation, ovarian epithelial cancer, quantitative characteristics, image registration, tumor visualization

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Authors: Mahesh Hariharan, Rajan Balasubramaniam, Sharath Kumar Shetty, Shanthala Yadavalli, Mohammed Ahetasham, Sravya Devarapalli

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Acute abdomen is one of the most common clinical conditions requiring a radiological investigation. Ultrasound is the primary modality of choice which can diagnose some of the common causes of acute abdomen. However, sometimes the underlying cause for the pain is far more complicated than expected to mandate a high degree of suspicion to suggest further investigation with contrast-enhanced computed tomography or magnetic resonance imaging. Here, we have compiled a comprehensive series of selected cases to highlight the conditions which can be easily overlooked unless carefully sought for. This also emphasizes the importance of multimodality approach to arrive at the final diagnosis with an increased overall diagnostic accuracy which in turn improves patient management and prognosis.

Keywords: acute abdomen, contrast-enhanced computed tomography scan, magnetic resonance imaging, plain radiographs, ultrasound

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Authors: Mouktafi Amine, Tahiri Asmaa

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A substantial number of traditional medical research has been put forward to managing and treating mental disorders. At the present time, to our best knowledge, it is believed that a fundamental understanding of the underlying causes of the majority of psychological disorders needs to be explored further to inform early diagnosis, managing symptoms and treatment. The emerging field of evolutionary psychology is a promising prospect to address the origin of mental disorders, potentially leading to more effective treatments. Schizophrenia as a topical mental disorder has been linked to the evolutionary adaptation of the human brain represented in the brain connectivity and asymmetry directly linked to humans' higher brain cognition in contrast to other primates being our direct living representation of the structure and connectivity of our earliest common African ancestors. As proposed in the evolutionary psychology scientific literature, the pathophysiology of schizophrenia is expressed and directly linked to altered connectivity between the Hippocampal Formation (HF) and Dorsolateral Prefrontal Cortex (DLPFC). This research paper presents the results of the use of tractography analysis using multiple open access Diffusion Weighted Imaging (DWI) datasets of healthy subjects, schizophrenia-affected subjects and primates to illustrate the relevance of the aforementioned brain regions' connectivity and the underlying evolutionary changes in the human brain. Deterministic fiber tracking and streamline analysis were used to generate connectivity matrices from the DWI datasets overlaid to compute distances and highlight disconnectivity patterns in conjunction with other fiber tracking metrics: Fractional Anisotropy (FA), Mean Diffusivity (MD) and Radial Diffusivity (RD).

Keywords: tractography, diffusion weighted imaging, schizophrenia, evolutionary psychology

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Authors: Raziyeh Mohammadi

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At present, nanoparticles are used for various biomedical applications where they facilitate laboratory diagnostics and therapeutics. The performance of nanoparticles for biomedical applications is often assessed by their narrow size distribution, suitable magnetic saturation, and low toxicity effects. Superparamagnetic iron oxide nanoparticles have received great attention due to their applications as contrast agents for magnetic resonance imaging (MRI. (Processes in the tissue where the blood brain barrier is intact in this way shielded from the contact to this conventional contrast agent and will only reveal changes in the tissue if it involves an alteration in the vasculature. This technique is very useful for detecting tumors and can even be used for detecting metabolic functional alterations in the brain, such as epileptic activity.SPIONs have found application in Magnetic Resonance Imaging (MRI) and magnetic hyperthermia. Unlike bulk iron, SPIONs do not have remnant magnetization in the absence of the external magnetic field; therefore, a precise remote control over their action is possible.

Keywords: nanoparticles, MRI, biomedical, iron oxide, spions

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Authors: Manal Alosaimi

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Many rehabilitation strategies exist to aid persons with neurological disorders relearn motor skills through intensive training. Evidence supporting the theory that cortical areas involved in motor execution can be triggered by observing actions performed by others is attributed to the function of the mirror neuron system (MNS) indicates that activation of the MNS is associated with improvements in physical action and motor learning. Therefore, it is important to investigate the relationship between motor training (in this case, playing the drums) and the activation of the MNS. To achieve this, 15 healthy right-handed participants received drum-kit training for 21 weeks, during which time blood oxygen level-dependent (BOLD) signals were monitored in the brain using functional magnetic resonance imaging (fMRI). Participants were required to perform action–observation and action–execution fMRI tasks. The main results are that BOLD signals in classical regions of the MNS such as supramarginal gyri, inferior parietal lobule, and supplementary motor area increase significantly over the training period. Activation of these areas indicates that passive-observation of others performing these same skills may facilitate recovery of persons suffering from neurological disorders, and complement conventional rehabilitation programs that focus on action execution or intense training.

Keywords: fMRI, mirror neuron system, magnetic resonance imaging, neuroplasticity, drumming, learning, music, action observation, action execution

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Authors: Paola Causin, Andrea Aspri, Alessandro Benfenati

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Diffuse Optical Tomography (DOT) is an emergent medical imaging technique which employs NIR light to estimate the spatial distribution of optical coefficients in biological tissues for diagnostic purposes, in a noninvasive and non-ionizing manner. DOT reconstruction is a severely ill-conditioned problem due to prevalent scattering of light in the tissue. In this contribution, we present our research in adopting hybrid knowledgedriven/data-driven approaches which exploit the existence of well assessed physical models and build upon them neural networks integrating the availability of data. Namely, since in this context regularization procedures are mandatory to obtain a reasonable reconstruction [1], we explore the use of neural networks as tools to include prior information on the solution. 2. Materials and Methods The idea underlying our approach is to leverage neural networks to solve PDE-constrained inverse problems of the form 𝒒 ∗ = 𝒂𝒓𝒈 𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃), (1) where D is a loss function which typically contains a discrepancy measure (or data fidelity) term plus other possible ad-hoc designed terms enforcing specific constraints. In the context of inverse problems like (1), one seeks the optimal set of physical parameters q, given the set of observations y. Moreover, 𝑦̃ is the computable approximation of y, which may be as well obtained from a neural network but also in a classic way via the resolution of a PDE with given input coefficients (forward problem, Fig.1 box ). Due to the severe ill conditioning of the reconstruction problem, we adopt a two-fold approach: i) we restrict the solutions (optical coefficients) to lie in a lower-dimensional subspace generated by auto-decoder type networks. This procedure forms priors of the solution (Fig.1 box ); ii) we use regularization procedures of type 𝒒̂ ∗ = 𝒂𝒓𝒈𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃)+ 𝑹(𝒒), where 𝑹(𝒒) is a regularization functional depending on regularization parameters which can be fixed a-priori or learned via a neural network in a data-driven modality. To further improve the generalizability of the proposed framework, we also infuse physics knowledge via soft penalty constraints (Fig.1 box ) in the overall optimization procedure (Fig.1 box ). 3. Discussion and Conclusion DOT reconstruction is severely hindered by ill-conditioning. The combined use of data-driven and knowledgedriven elements is beneficial and allows to obtain improved results, especially with a restricted dataset and in presence of variable sources of noise.

Keywords: inverse problem in tomography, deep learning, diffuse optical tomography, regularization

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Authors: Asima Mehaboob Khan, Rizwan Taj

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Purpose: This study aims to estimate the knowledge, attitude and practices of medical ethics among young healthcare professionals. Method: A qualitative descriptive study was conducted among young healthcare professionals from both public and private sector medical institutions. Using the convenience sampling technique, 272 healthcare professionals participated in this study. A pre-structured modified questionnaire was used to collect the data. Descriptive analyses were executed for each variable. Result: About 76.47% of healthcare professional considers the importance of adequate knowledge of medical ethics, and 82.24% declared lecture, seminars and clinical discussion as the source of their medical knowledge of biomedical ethics. About 42.44% of healthcare professionals exhibited a negative attitude toward medical ethics, 57.72% showed a mildly positive attitude, whereas 1.10% and 0.74% indicated a moderately positive attitude and a highly positive attitude towards medical ethics. Similarly, the level of practice according to medical ethics is also very poor among young healthcare professionals. 34.56% of healthcare professionals deviated from medical ethics during their clinical practices, whereas 0.74% showed a good level of medical practice according to medical ethics. Conclusion: It is concluded in this research study that young healthcare professionals have adequate theoretical knowledge of medical ethics but are not properly trained to perform their clinical practices according to the guidelines of medical ethics. Furthermore, their professional attitude is poorly developed to maintain medical ethics during their clinical practices.

Keywords: knowledge, attitude, practices, medical ethics

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Authors: Kohei Shimasaki, Tomoaki Okamura, Idaku Ishii

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We propose a vibration imaging method for high frame rate (HFR)-video-based localization of vibrating objects with large translations. When the ratio of the translation speed of a target to its vibration frequency is large, obtaining its frequency response in image intensities becomes difficult because one or no waves are observable at the same pixel. Our method can precisely localize moving objects with vibration by virtually translating multiple image sequences for pixel-level short-time Fourier transform to observe multiple waves at the same pixel. The effectiveness of the proposed method is demonstrated by analyzing several HFR videos of flying insects in real scenarios.

Keywords: HFR video analysis, pixel-level vibration source localization, short-time Fourier transform, virtual translation

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Authors: David Oluigbo, Erik Hemberg, Nathan Shwatal, Wenqi Ding, Yin Yuan, Susanna Mierau

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Introduction: Calcium imaging is an established technique in neuroscience research for detecting activity in neural networks. Bursts of action potentials in neurons lead to transient increases in intracellular calcium visualized with fluorescent indicators. Manual identification of cell bodies and their contours by experts typically takes 10-20 minutes per calcium imaging recording. Our aim, therefore, was to design an automated pipeline to facilitate and optimize calcium imaging data analysis. Our pipeline aims to accelerate cell body and contour identification and production of graphical representations reflecting changes in neuronal calcium-based fluorescence. Methods: We created a Python-based pipeline that uses OpenCV (a computer vision Python package) to accurately (1) detect neuron contours, (2) extract the mean fluorescence within the contour, and (3) identify transient changes in the fluorescence due to neuronal activity. The pipeline consisted of 3 Python scripts that could both be easily accessed through a Python Jupyter notebook. In total, we tested this pipeline on ten separate calcium imaging datasets from murine dissociate cortical cultures. We next compared our automated pipeline outputs with the outputs of manually labeled data for neuronal cell location and corresponding fluorescent times series generated by an expert neuroscientist. Results: Our results show that our automated pipeline efficiently pinpoints neuronal cell body location and neuronal contours and provides a graphical representation of neural network metrics accurately reflecting changes in neuronal calcium-based fluorescence. The pipeline detected the shape, area, and location of most neuronal cell body contours by using binary thresholding and grayscale image conversion to allow computer vision to better distinguish between cells and non-cells. Its results were also comparable to manually analyzed results but with significantly reduced result acquisition times of 2-5 minutes per recording versus 10-20 minutes per recording. Based on these findings, our next step is to precisely measure the specificity and sensitivity of the automated pipeline’s cell body and contour detection to extract more robust neural network metrics and dynamics. Conclusion: Our Python-based pipeline performed automated computer vision-based analysis of calcium image recordings from neuronal cell bodies in neuronal cell cultures. Our new goal is to improve cell body and contour detection to produce more robust, accurate neural network metrics and dynamic graphs.

Keywords: calcium imaging, computer vision, neural activity, neural networks

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Authors: Fatima M. Jadu, Asmaa A. Alzahrani, Maha A. Almutairi, Salma O. Al-Amoudi, Mawya A. Khafaji

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Introduction: Estimating the potential radiation risk for a widely used imaging technique such as cone beam CT (CBCT) is crucial. The aim of this study was to examine the effect of varying two CBCT technical factors, the voxel size (VOX) and the Field-of-View (FOV) centralization, on the radiation dose. Methodology: The head and neck slices of a RANDO® man phantom (Alderson Research Laboratories) were used with nanoDot™ OSLD dosimeters to measure the absorbed radiation dose at 25 predetermined sites. Imaging was done using the i-CAT® (Imaging Science International, Hatfield, PA, USA) CBCT unit. The VOX was changed for every three cycles of exposures from 0.2mm to 0.3mm and then 0.4mm. Then the FOV was centered on the maxilla and mandible alternatively while holding all other factors constant. Finally, the effective radiation dose was calculated for each view and voxel setting. Results: The effective radiation dose was greatest when the smallest VOX was chosen. When the FOV was centered on the maxilla, the highest radiation doses were recorded in the eyes and parotid glands. While on the mandible, the highest radiation doses were recorded in the sublingual and submandibular glands. Conclusion: Minor variations in the CBCT exposure factors significantly affect the effective radiation dose and thus the radiation risk to the patient. Therefore, extreme care must be taken when choosing these parameters especially for vulnerable patients such as children.

Keywords: CBCT, cone beam CT, effective dose, field of view, mandible, maxilla, resolution, voxel

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Authors: H. Yousefnia, S. Zolghadri

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An early diagnosis of bone metastases is very important for providing a profound decision on a subsequent therapy. A prerequisite for the clinical application of new diagnostic radiopharmaceutical is the measurement of organ radiation exposure dose from biodistribution data in animals. In this study, the dosimetric studies of a novel agent for SPECT-imaging of bone methastases, 111In-(4-{[(bis(phosphonomethyl))carbamoyl]methyl}-7,10-bis(carboxymethyl)-1,4,7,10-tetraazacyclododec-1-yl) acetic acid (111In-BPAMD) complex, have been estimated in human organs based on mice data. The radiolabeled complex was prepared with high radiochemical purity at the optimal conditions. Biodistribution studies of the complex were investigated in male Syrian mice at selected times after injection (2, 4, 24 and 48 h). The human absorbed dose estimation of the complex was performed based on mice data by the radiation absorbed dose assessment resource (RADAR) method. 111In-BPAMD complex was prepared with high radiochemical purity >95% (ITLC) and specific activities of 2.85 TBq/mmol. Total body effective absorbed dose for 111In-BPAMD was 0.205 mSv/MBq. This value is comparable to the other 111In clinically used complexes. The results show that the dose to critical organs the complex is well within the acceptable considered range for diagnostic nuclear medicine procedures. Generally, 111In-BPAMD has interesting characteristics and can be considered as a viable agent for SPECT-imaging of the bone metastases in the near future.

Keywords: In-111, BPAMD, absorbed dose, RADAR

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Authors: N. Tadayon, H. Yousefnia, S. Zolghadri, A. Ramazani, A. R. Jalilian

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Bone metastases occur in many patients with solid malignant tumors. Recently, 1,2 propylene di-amino tetra methylenephosphonic acid (PDTMP) has been introduced as a suitable carrier in the development of therapeutic bone-avid radiopharmaceuticals. In this study, due to the desirable characteristics of 68Ga, 68Ga-PDTMP was prepared. 68Ga was obtained from SnO2 based generator. A stock solution of PDTMP was prepared by dissolving in 2 N NaOH. A certain volume of the stock solution was added to the vial containing 68GaCl3 and the pH of the mixture was adjusted to 4 using HEPES. Radiochemical purity of the radiolabelled complex was checked by thin layer chromatography. 68Ga-PDTMP was prepared in only 15 min with radiochemical purity of more than 98%. This new bone-seeking complex can be considered as a good candidate of PET-based radiopharmaceutical for imaging of bone metastases.

Keywords: bone metastases, Ga-68, imaging, PDTMP

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Authors: Ashfaq M. Naikwadi

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Decided cases of medical negligence, mostly are not settled in the lower courts. Majority of them reach up to the apex courts. This is mostly due to different interpretations of the term medical negligence. After studying various cases of medical negligence it is found that in most of the cases the doctors/hospitals are not held liable. There are different interpretations of law concerning medical services. Globally the principles deciding medical negligence are same, viz. Legal duty of care - breach of that duty - direct causation resulting in damages. Since ordinary negligence is not punishable by law, doctors/hospitals have defenses to save themselves from liability. Complaints of negligence come to the courts whose judges mostly are not oriented with medical services or health sciences. Matters of medical negligence are decided on the basic principles of reasonableness and prudence or by relying on the expert’s opinion. Deciding reasonableness or prudence is a complex issue in case of medical services. Again expert opinion is also questionable as an expert in case of medical negligence is appointed from the same field and same faculty. There is a chance of favoritism to the doctor/hospital. The concept of vicarious liability is not widely applied to in many of the medical negligence cases. Established cases used as precedents were studied to understand the basic principles in deciding medical negligence. This paper evaluates the present criteria in interpreting medical negligence and concludes with suggesting reforms required to be made in deciding matters of medical negligence under the consumer laws.

Keywords: consumer, doctors, laws, medical negligence

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Authors: Mehwish Asghar

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Breast Cancer (BC) is a common type of cancer among women. Its screening is usually performed using different imaging modalities such as magnetic resonance imaging, mammogram, X-ray, CT, etc. Among these modalities’ mammogram is considered a powerful tool for diagnosis and screening of breast cancer. Sophisticated machine learning approaches have shown promising results in complementing human diagnosis. Generally, machine learning methods can be divided into two major classes: one is Radiomics analysis (RA), where image features are extracted manually; and the other one is the concept of convolutional neural networks (CNN), in which the computer learns to recognize image features on its own. This research aims to improve the incidence of early detection, thus reducing the mortality rate caused by breast cancer through the latest advancements in computer science, in general, and machine learning, in particular. It has also been aimed to ease the burden of doctors by improving and automating the process of breast cancer detection. This research is related to a relative analysis of different techniques for the implementation of different models for detecting and classifying breast cancer. The main goal of this research is to provide a detailed view of results and performances between different techniques. The purpose of this paper is to explore the potential of a convolutional neural network (CNN) w.r.t feature extractor and as a classifier. Also, in this research, it has been aimed to add the module of Radiomics for comparison of its results with deep learning techniques.

Keywords: breast cancer (BC), machine learning (ML), convolutional neural network (CNN), radionics, magnetic resonance imaging, artificial intelligence

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Authors: Shahrzad Zolfagharnassab, Abdul Rashid Mohamed Shariff, Reza Ehsani, Hawa Ze Jaffar, Ishak Aris

Abstract:

Ripeness estimation of oil palm fresh fruit is important processes that affect the profitableness and salability of oil palm fruits. The adulthood or ripeness of the oil palm fruits influences the quality of oil palm. Conventional procedure includes physical grading of Fresh Fruit Bunches (FFB) maturity by calculating the number of loose fruits per bunch. This physical classification of oil palm FFB is costly, time consuming and the results may have human error. Hence, many researchers try to develop the methods for ascertaining the maturity of oil palm fruits and thereby, deviously the oil content of distinct palm fruits without the need for exhausting oil extraction and analysis. This research investigates the potential of infrared images (Thermal Images) as a predictor to classify the oil palm FFB ripeness. A total of 270 oil palm fresh fruit bunches from most common cultivar of oil palm bunches Nigresens according to three maturity categories: under ripe, ripe and over ripe were collected. Each sample was scanned by the thermal imaging cameras FLIR E60 and FLIR T440. The average temperature of each bunches were calculated by using image processing in FLIR Tools and FLIR ThermaCAM researcher pro 2.10 environment software. The results show that temperature content decreased from immature to over mature oil palm FFBs. An overall analysis-of-variance (ANOVA) test was proved that this predictor gave significant difference between underripe, ripe and overripe maturity categories. This shows that the temperature as predictors can be good indicators to classify oil palm FFB. Classification analysis was performed by using the temperature of the FFB as predictors through Linear Discriminant Analysis (LDA), Mahalanobis Discriminant Analysis (MDA), Artificial Neural Network (ANN) and K- Nearest Neighbor (KNN) methods. The highest overall classification accuracy was 88.2% by using Artificial Neural Network. This research proves that thermal imaging and neural network method can be used as predictors of oil palm maturity classification.

Keywords: artificial neural network, maturity classification, oil palm FFB, thermal imaging

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Authors: M. Vimal Raj, S. Sakthivel Murugan

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Underwater images degrade their quality due to atmospheric conditions. One of the major problems in an underwater image is motion blur caused by the imaging device or the movement of the object. In order to rectify that in post-imaging, parameters of the blurred image are to be estimated. So, the point spread function is estimated by the properties, using the spectrum of the image. To improve the estimation accuracy of the parameters, Optimized Polynomial Lagrange Interpolation (OPLI) method is implemented after the angle and length measurement of motion-blurred images. Initially, the data were collected from real-time environments in Chennai and processed. The proposed OPLI method shows better accuracy than the existing classical Cepstral, Hough, and Radon transform estimation methods for underwater images.

Keywords: image restoration, motion blur, parameter estimation, radon transform, underwater

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Authors: Leping Chen, Daoxiang An, Xiaotao Huang

Abstract:

Automatic vehicle detection using synthetic aperture radar (SAR) image has been widely researched, as well as using optical remote sensing images. However, most researches treat the detection as an independent problem, failing to make full use of SAR data information. In circular SAR (CSAR), the two long borders of vehicle will shrink if the imaging surface is set higher than the reference one. Based on above variance, an automatic vehicle detection using CSAR image is proposed to enhance detection ability under complex environment, such as vehicles’ closely packing, which confuses the detector. The detection method uses the multiple images generated by different height plane to obtain an energy-concentrated image for detecting and then uses the maximally stable extremal regions method (MSER) to detect vehicles. A result of vehicles’ detection is given to verify the effectiveness and correctness of proposed method.

Keywords: circular SAR, vehicle detection, automatic, imaging

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Authors: M. S. Sukumar

Abstract:

Our objective is to develop a full-fledged system for exploring and studying nature of fossils and to extend this to underwater archaeology and mineral mapping. This includes aerial surveying, imaging techniques, artefact extraction and spectrum analysing techniques. These techniques help in regular monitoring of fossils and also the sensing system. The ROV was designed to complete several tasks which simulate collecting data and samples. Given the time constraints, the ROV was engineered for efficiency and speed in performing tasks. Its other major design consideration was modularity, allowing the team to distribute the building process, to easily test systems as they were completed and troubleshoot and replace systems as necessary. Our design itself had several challenges of on-board waterproofed sensor mounting, waterproofing of motors, ROV stability criteria, camera mounting and hydrophone sound acquisition.

Keywords: remotely operated vehicle (ROV) dragonair, underwater archaeology, full-fledged system, aerial imaging and detection

Procedia PDF Downloads 239

Authors: Sonia Mahajan Dinesh, Anant Dinesh, Madhavi Tripathi, Vinod Kumar Ramteke, Rajnish Sharma, Anupam Mondal

Abstract:

Background: Neo-adjuvant chemotherapy plays an important role in treatment of breast cancer by decreasing the tumour load and it offers an opportunity to evaluate response of primary tumour to chemotherapy. Standard anatomical imaging modalities are unable to accurately reflect the response to chemotherapy until several cycles of drug treatment have been completed. Metabolic imaging using tracers like 18F-fluorodeoxyglucose (FDG) as a marker of glucose metabolism or amino acid tracers like L-methyl-11C methionine (MET) have potential role for the measurement of treatment response. In this study, our objective was to compare these two PET tracers for assessment of response to neoadjuvant chemotherapy, in locally advanced breast carcinoma. Methods: In our prospective study, 20 female patients with histology proven locally advanced breast carcinoma underwent PET-CT imaging using FDG and MET before and after three cycles of neoadjuvant chemotherapy (CAF regimen). Thereafter, all patients were taken for MRM and the resected specimen was sent for histo-pathological analysis. Tumour response to the neoadjuvant chemotherapy was evaluated by PET-CT imaging using PERCIST criteria and correlated with histological results. Responses calculated were compared for statistical significance using paired t- test. Results: Mean SUVmax for primary lesion in FDG PET and MET PET was 15.88±11.12 and 5.01±2.14 respectively (p<0.001) and for axillary lymph nodes was 7.61±7.31 and 2.75±2.27 respectively (p=0.001). Statistically significant response in primary tumour and axilla was noted on both FDG and MET PET after three cycles of NAC. Complete response in primary tumour was seen in only 1 patient in FDG and 7 patients in MET PET (p=0.001) whereas there was no histological complete resolution of tumor in any patient. Response to therapy in axillary nodes noted on both PET scans were similar (p=0.45) and correlated well with histological findings. Conclusions: For the primary breast tumour, FDG PET has a higher sensitivity and accuracy than MET PET and for axilla both have comparable sensitivity and specificity. FDG PET shows higher target to background ratios so response is better predicted for primary breast tumour and axilla. Also, FDG-PET is widely available and has the advantage of a whole body evaluation in one study.

Keywords: 11C-methionine, 18F-FDG, breast carcinoma, neoadjuvant chemotherapy

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Authors: Hary Aprianto Wijaya Siahaan, Bayu Edo Pratama

Abstract:

Sea fishery's potential to become one of the nation's assets which very contributed to Indonesia's economy. This fishery potential not in spite of the availability of the chlorophyll in the territorial waters of Indonesia. The research was conducted using three methods, namely: statistics, comparative and analytical. The data used include MODIS sea temperature data imaging results in Aqua satellite with a resolution of 4 km in 2002-2015, MODIS data of chlorophyll-a imaging results in Aqua satellite with a resolution of 4 km in 2002-2015, and Imaging results data ASCAT on MetOp and NOAA satellites with 27 km resolution in 2002-2015. The results of the processing of the data show that the incidence of upwelling in the south of East Java Sea began to happen in June identified with sea surface temperature anomaly below normal, the mass of the air that moves from the East to the West, and chlorophyll-a concentrations are high. In July the region upwelling events are increasingly expanding towards the West and reached its peak in August. Chlorophyll-a concentration prediction using multiple linear regression equations demonstrate excellent results to chlorophyll-a concentrations prediction in 2002 until 2015 with the correlation of predicted chlorophyll-a concentration indicate a value of 0.8 and 0.3 with RMSE value. On the chlorophyll-a concentration prediction in 2016 indicate good results despite a decline in the value of the correlation, where the correlation of predicted chlorophyll-a concentration in the year 2016 indicate a value 0.6, but showed improvement in RMSE values with 0.2.

Keywords: satellite, sea surface temperature, upwelling, wind stress

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Authors: Samira-Sadat JamaliDinan, Haidar Almohri, Mohammad-Reza Nazem-Zadeh

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Lateralization of temporal lobe epilepsy (TLE) is very important for positive surgical outcomes. We propose a machine learning framework to ultimately identify the epileptogenic hemisphere for temporal lobe epilepsy (TLE) cases using magnetoencephalography (MEG) coherence source imaging (CSI) and diffusion tensor imaging (DTI). Unlike most studies that use classification algorithms, we propose an effective clustering approach to distinguish between normal and TLE cases. We apply the famous Minkowski weighted K-Means (MWK-Means) technique as the clustering framework. To overcome the problem of poor initialization of K-Means, we use particle swarm optimization (PSO) to effectively select the initial centroids of clusters prior to applying MWK-Means. We demonstrate that compared to K-means and MWK-means independently, this approach is able to improve the result of a benchmark data set.

Keywords: temporal lobe epilepsy, machine learning, clustering, magnetoencephalography

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Authors: Aljon Pangan

Abstract:

The Philippines being an archipelagic country, is surrounded by coastlines (36,289 km), coastal waters (226,000 km²), oceanic waters (1.93 million km²) and territorial waters (2.2 million km²). Studies show that the Philippine coastal ecosystems are the most productive and biologically diverse in the world, however, plagued by degradation problems due to over-exploitation and illegal activities. The existence of coastal degradation issues in the country led to the emergence of Coastal Resource Management (CRM) as an approach to both national and local government in providing solutions for sustainable coastal resource utilization. CRM applies the idea of planning, implementing and monitoring through the lens of collaborative governance. It utilizes collective action and decision-making to achieve sustainable use of coastal resources. The Municipality of Bagac in Bataan is one of the coastal municipalities in the country who crafts its own CRM Program as a solution to coastal resource degradation and problems. Information and Communications Technology (ICT), particularly Integrated Imaging Management System (IIMS) is one approach that can be applied in the formula of collaborative governance which entails the Government, Private Sector, and Civil Society. IIMS can help policymakers, managers, and citizens in managing coastal resources through analyzed spatial data describing the physical, biological, and socioeconomic characteristics of the coastal areas. Moreover, this study will apply the qualitative approach in deciphering possible impacts of the application of IIMS in the Coastal Resource Management policy making and implementation of the Municipality of Bagac.

Keywords: coastal resource management, collaborative governance, integrated imaging management system, information and communication technology

Procedia PDF Downloads 400