Computer Vision & Robotics

This is a short description of the theme

Latest Related Publications

View All Publications
Nikhil Kumar Tomar, Debesh Jha, Ulas Bagci, Sharib Ali
TGANet: Text-guided attention for improved polyp segmentation
Medical Image Computing and Computer Assisted Intervention – MICCAI, 2022

author="Tomar, Nikhil Kumar
and Jha, Debesh
and Bagci, Ulas
and Ali, Sharib",
editor="Wang, Linwei
and Dou, Qi
and Fletcher, P. Thomas
and Speidel, Stefanie
and Li, Shuo",
title="TGANet: Text-Guided Attention for Improved Polyp Segmentation",
booktitle="Medical Image Computing and Computer Assisted Intervention -- MICCAI 2022",
publisher="Springer Nature Switzerland",
abstract="Colonoscopy is a gold standard procedure but is highly operator-dependent. Automated polyp segmentation, a precancerous precursor, can minimize missed rates and timely treatment of colon cancer at an early stage. Even though there are deep learning methods developed for this task, variability in polyp size can impact model training, thereby limiting it to the size attribute of the majority of samples in the training dataset that may provide sub-optimal results to differently sized polyps. In this work, we exploit size-related and polyp number-related features in the form of text attention during training. We introduce an auxiliary classification task to weight the text-based embedding that allows network to learn additional feature representations that can distinctly adapt to differently sized polyps and can adapt to cases with multiple polyps. Our experimental results demonstrate that these added text embeddings improve the overall performance of the model compared to state-of-the-art segmentation methods. We explore four different datasets and provide insights for size-specific improvements. Our proposed text-guided attention network (TGANet) can generalize well to variable-sized polyps in different datasets. Codes are available at",

Sharib Ali, Noha Ghatwary, Debesh Jha, Ece Isik-Polat, Gorkem Polat, Chen Yang, Wuyang Li, Adrian Galdran, Miguel-Ángel González Ballester, Vajira Thambawita, Steven Hicks, Sahadev Poudel, Sang-Woong Lee, Ziyi Jin, Tianyuan Gan, ChengHui Yu, JiangPeng Yan, Doyeob Yeo, Hyunseok Lee, Nikhil Kumar Tomar, Mahmood Haithmi, Amr Ahmed, Michael A. Riegler, Christian Daul, Pål Halvorsen, Jens Rittscher, Osama E. Salem, Dominique Lamarque, Renato Cannizzaro, Stefano Realdon, Thomas de Lange, James E. East
Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge

  title={Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge},
  author={Ali, Sharib and Ghatwary, Noha and Jha, Debesh and Isik-Polat, Ece and Polat, Gorkem and Yang, Chen and Li, Wuyang and Galdran, Adrian and Ballester, Miguel-{\'A}ngel Gonz{\'a}lez and Thambawita, Vajira and others},
  journal={arXiv preprint arXiv:2202.12031},

Latest Related News

View All News

Research Paper Accepted at ICPR 2022

April 26, 2022

We are pleased to inform that the “ Label Geometry Aware Discriminator for Conditional Generative Networks ” research paper is accepted at ICPR 2022. The research was led by Dr. […]

Read More

Latest Related Blogs

View All Blogs

Nothing Found

There are no content in this category for this theme. Please check again later , or try a different theme