27 citations · 32 across the 12 of their papers we have counts for
7 papers · 1 filter
Multi-Scale Fusion Methodologies for Head and Neck Tumor Segmentation
Abhishek Srivastava, Debesh Jha, Bulent Aydogan +2
Head and Neck (H\&N) organ-at-risk (OAR) and tumor segmentations are essential components of radiation therapy planning. The varying anatomic locations and dimensions of H\&N nodal…
An Efficient Multi-Scale Fusion Network for 3D Organ at Risk (OAR) Segmentation
Abhishek Srivastava, Debesh Jha, Elif Keles +3
Accurate segmentation of organs-at-risks (OARs) is a precursor for optimizing radiation therapy planning. Existing deep learning-based multi-scale fusion architectures have demonst…
Automatic Polyp Segmentation with Multiple Kernel Dilated Convolution Network
Nikhil Kumar Tomar, Abhishek Srivastava, Ulas Bagci +1
The detection and removal of precancerous polyps through colonoscopy is the primary technique for the prevention of colorectal cancer worldwide. However, the miss rate of colorecta…
Video Capsule Endoscopy Classification using Focal Modulation Guided Convolutional Neural Network
Abhishek Srivastava, Nikhil Kumar Tomar, Ulas Bagci +1
Video capsule endoscopy is a hot topic in computer vision and medicine. Deep learning can have a positive impact on the future of video capsule endoscopy technology. It can improve…
PAANet: Progressive Alternating Attention for Automatic Medical Image Segmentation
Abhishek Srivastava, Sukalpa Chanda, Debesh Jha +4
Medical image segmentation can provide detailed information for clinical analysis which can be useful for scenarios where the detailed location of a finding is important. Knowing t…
GMSRF-Net: An improved generalizability with global multi-scale residual fusion network for polyp segmentation
Abhishek Srivastava, Sukalpa Chanda, Debesh Jha +2
Colonoscopy is a gold standard procedure but is highly operator-dependent. Efforts have been made to automate the detection and segmentation of polyps, a precancerous precursor, to…
MSRF-Net: A Multi-Scale Residual Fusion Network for Biomedical Image Segmentation
Abhishek Srivastava, Debesh Jha, Sukalpa Chanda +6
Methods based on convolutional neural networks have improved the performance of biomedical image segmentation. However, most of these methods cannot efficiently segment objects of…