Blar i NTNU Open på forfatter "Survarachakan, Shanmugapriya"
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Deep learning for image-based liver analysis — A comprehensive review focusing on malignant lesions
Survarachakan, Shanmugapriya; Prasad, Pravda Jith Ray; Naseem, Rabia; Perez de Frutos, Javier; Kumar, Rahul Prasanna; Langø, Thomas; Alaya Cheikh, Faouzi; Elle, Ole Jakob; Lindseth, Frank (Peer reviewed; Journal article, 2022)Deep learning-based methods, in particular, convolutional neural networks and fully convolutional networks are now widely used in the medical image analysis domain. The scope of this review focuses on the analysis using ... -
Effects of enhancement on deep learning based hepatic vessel segmentation
Survarachakan, Shanmugapriya; Pelanis, Egidijius; Khan, Zohaib Amjad; Kumar, Rahul Prasanna; Edwin, Bjørn; Lindseth, Frank (Journal article; Peer reviewed, 2021) -
Learning deep abdominal CT registration through adaptive loss weighting and synthetic data generation
Perez de Frutos, Javier; Pedersen, Andre; Pelanis, Egidijus; Bouget, David Nicolas Jean-Mar; Survarachakan, Shanmugapriya; Langø, Thomas; Elle, Ole Jakob; Lindseth, Frank (Peer reviewed; Journal article, 2023)Purpose This study aims to explore training strategies to improve convolutional neural network-based image-to-image deformable registration for abdominal imaging. Methods Different training strategies, loss functions, and ... -
Numerical evaluation on parametric choices influencing segmentation results in radiology images—a multi-dataset study
Prasad, Pravda Jith Ray; Survarachakan, Shanmugapriya; Khan, Zohaib Amjad; Lindseth, Frank; Elle, Ole Jacob; Albregtsen, Fritz; Kumar, Rahul Prasanna (Peer reviewed; Journal article, 2021)Medical image segmentation has gained greater attention over the past decade, especially in the field of image-guided surgery. Here, robust, accurate and fast segmentation tools are important for planning and navigation. ...