Search results for: intraspecific variability

Authors: Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Kensuke Nakamura, Dongeun Choi, Byung-Woo Hong

Abstract:

Artefacts are commonly encountered in the imaging process of clinical computed tomography (CT) where the artefact refers to any systematic discrepancy between the reconstructed observation and the true attenuation coefficient of the object. It is known that CT images are inherently more prone to artefacts due to its image formation process where a large number of independent detectors are involved, and they are assumed to yield consistent measurements. There are a number of different artefact types including noise, beam hardening, scatter, pseudo-enhancement, motion, helical, ring, and metal artefacts, which cause serious difficulties in reading images. Thus, it is desired to remove nuisance factors from the degraded image leaving the fundamental intrinsic information that can provide better interpretation of the anatomical and pathological characteristics. However, it is considered as a difficult task due to the high dimensionality and variability of data to be recovered, which naturally motivates the use of machine learning techniques. We propose an image restoration algorithm based on the deep neural network framework where the denoising auto-encoders are stacked building multiple layers. The denoising auto-encoder is a variant of a classical auto-encoder that takes an input data and maps it to a hidden representation through a deterministic mapping using a non-linear activation function. The latent representation is then mapped back into a reconstruction the size of which is the same as the size of the input data. The reconstruction error can be measured by the traditional squared error assuming the residual follows a normal distribution. In addition to the designed loss function, an effective regularization scheme using residual-driven dropout determined based on the gradient at each layer. The optimal weights are computed by the classical stochastic gradient descent algorithm combined with the back-propagation algorithm. In our algorithm, we initially decompose an input image into its intrinsic representation and the nuisance factors including artefacts based on the classical Total Variation problem that can be efficiently optimized by the convex optimization algorithm such as primal-dual method. The intrinsic forms of the input images are provided to the deep denosing auto-encoders with their original forms in the training phase. In the testing phase, a given image is first decomposed into the intrinsic form and then provided to the trained network to obtain its reconstruction. We apply our algorithm to the restoration of the corrupted CT images by the artefacts. It is shown that our algorithm improves the readability and enhances the anatomical and pathological properties of the object. The quantitative evaluation is performed in terms of the PSNR, and the qualitative evaluation provides significant improvement in reading images despite degrading artefacts. The experimental results indicate the potential of our algorithm as a prior solution to the image interpretation tasks in a variety of medical imaging applications. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: auto-encoder neural network, CT image artefact, deep learning, intrinsic image representation, noise reduction, total variation

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Authors: Divya SY. Ang, Mark B. Tan, Nicholas EM. Yeo, Siti RB. Sudirman, Khong Yik Chew

Abstract:

Introduction: The importance of the amalgamation of technological and engineering advances with surgical principles of reconstruction cannot be overemphasized. With earlier detection of cancer, consequences of high-speed living and neglect, like traumatic injuries and infection, resulting in increasingly younger patients with bone defects. This may result in malformations and suboptimal function that is more noticeable and palpable in the younger, active demographic. Our team proposes a technique that encapsulates a mesh of multidisciplinary effort, tissue engineering and reconstructive principles. Methods/Materials: Our patient was a young competitive footballer in his early 30s who was diagnosed with submandibular adenoid cystic carcinoma with bony involvement. He was thus counselled for a right hemi mandibulectomy, the floor of mouth resection, right selective neck dissection, tracheostomy, and free fibular flap reconstruction of his mandible and required post-operative radiotherapy. Being young and in his prime sportsman years, he was unable to accept the morbidities associated with using his fibula to reconstruct his mandible despite it being the gold standard reconstructive option. The fibula is an ideal vascularized bone flap because it’s reliable and easily shaped with relatively minimal impact on functional outcomes. The fibula contributes to 30% of weightbearing and is the attachment for the lateral compartment muscles; it is stronger in footballers concerning lateral bending. When harvesting the fibula, the distal 6-8cm and up to 10% of the total length is preserved to maintain the ankle’s stability, thus, minimizing the impact on daily activities. There are studies that have noted gait variability post-operatively. Therefore, returning to a premorbid competitive level may be doubtful. To improve his functional outcomes, the decision was made to try and restore the fibula's form and function. Using the concept of Fused Deposition Modelling (FDM), our team comprising of Plastics, Otolaryngology, Orthopedics and Radiology, worked with Osteopore to design a 3D bioresorbable implant to regenerate the fibula defect (14.5cm). Bone marrow was harvested via reaming the contralateral hip prior to the wide resection. 30mls of his blood was obtained for extracting platelet rich plasma. These were packed into the Osteopore 3D-printed bone scaffold. This was then secured into the fibula defect with titanium plates and screws. The flexor hallucis longus and soleus were anchored along the construct and intraosseous membrane, done in a single setting. Results: He was reviewed closely as an outpatient over 10 months post operatively. He reported no discernable loss or difference in ankle function. He is satisfied and back in training and our team has video and photographs that substantiate his progress. Conclusion: FDM allows regeneration of long bone defects. However, we aimed to also restore his eversion and inversion that is imperative for footballers and hence reattached his previously dissected muscles along the length of the Osteopore implant. We believe that the reattachment of the muscle stabilizes not only the construct but allows optimum muscle tensioning when moving his ankle. This is a simple but effective technique in restoring complete function and form in a young patient whose minute muscle control is imperative to life.

Keywords: fused deposition modelling, functional reconstruction, lower limb bony defects, regenerative surgery, 3D printing, tissue engineering

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Authors: Mara Getachew Zenebe, Luuk Fleskens, Abdu Obieda Ahmed

Abstract:

This paper seeks to advance our scientific understanding of optimizing flood utilization in regions impacted by climate change, with a focus on enhancing agricultural productivity through effective irrigation management. The study was conducted as part of a three-year (2021 to 2023) USAID-supported initiative aimed at promoting Economic Growth and Peace in the Gash Agricultural Scheme (GAS), situated in Sudan's water-stressed Eastern region. GAS is the country's largest flood-irrigated scheme, covering 100,800 hectares of cultivable land, with a potential to provide the food security needs of over a quarter of a million agro-pastoral community members. GAS relies on the Gash River, which sources its water from high-intensity rainfall events in the highlands of Ethiopia and Eritrea. However, climate change and variations in these highlands have led to increased variability in the Gash River's flow. The study conducted water balance analyses based on a ten-year dataset of the annual Gash River flow, irrigated area; as well as the evapotranspiration demand of the major sorghum crop. Data collection methods included field measurements, surveys, remote sensing, and CropWat modelling. The water balance assessment revealed that the existing three-year rotation-based irrigation system management, capping cultivated land at 33,000 hectares annually, is excessively risk-averse. While this system reduced conflicts among the agro-pastoral communities by consistently delivering on the land promised to be annually cultivated, it also increased GAS's vulnerability to flood damage due to several reasons. The irrigation efficiency over the past decade was approximately 30%, leaving significant unharnessed floodwater that caused damage to infrastructure and agricultural land. The three-year rotation resulted in inadequate infrastructural maintenance, given the destructive nature of floods. Additionally, it led to infrequent land tillage, allowing the encroachment of mesquite trees hindering major sorghum crop growth. Remote sensing data confirmed that mesquite trees have overtaken 70,000 hectares in the past two decades, rendering them unavailable for agriculture. The water balance analyses suggest shifting to a two-year rotation, covering approximately 50,000 hectares annually while maintaining risk aversion. This shift could boost GAS's annual sorghum production by two-thirds, exceeding 850,000 tons. The scheme's efficiency can be further enhanced through low-cost on-farm interventions. Currently, large irrigation plots that range from 420 to 756 hectares are irrigated with limited water distribution guidance, leading to uneven irrigation. As demonstrated through field trials, implementing internal longitudinal bunds and horizontal deflector bunds can increase adequately irrigated parts of the irrigation plots from 50% to 80% and thus nearly double the sorghum yield to 2 tons per hectare while reducing the irrigation duration from 30 days to a maximum of 17 days. Flow measurements in 2021 and 2022 confirmed that these changes sufficiently meet the sorghum crop's water requirements, even with a conservative 60% field application efficiency assumption. These insights and lessons from the GAS on enhancing agricultural resilience and sustainability in the face of climate change are relevant to flood-based livelihood systems globally.

Keywords: climate change, irrigation management and productivity, variable flood flows, water balance analysis

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