103 citations · 349 across the 55 of their papers we have counts for
15 papers · 1 filter
Robustness Stress Testing in Medical Image Classification
Mobarakol Islam, Zeju Li, Ben Glocker
Deep neural networks have shown impressive performance for image-based disease detection. Performance is commonly evaluated through clinical validation on independent test sets to…
CAT-ViL: Co-Attention Gated Vision-Language Embedding for Visual Question Localized-Answering in Robotic Surgery
Long Bai, Mobarakol Islam, Hongliang Ren
Medical students and junior surgeons often rely on senior surgeons and specialists to answer their questions when learning surgery. However, experts are often busy with clinical an…
SAM Meets Robotic Surgery: An Empirical Study on Generalization, Robustness and Adaptation
An Wang, Mobarakol Islam, Mengya Xu +2
The Segment Anything Model (SAM) serves as a fundamental model for semantic segmentation and demonstrates remarkable generalization capabilities across a wide range of downstream s…
Landmark Detection using Transformer Toward Robot-assisted Nasal Airway Intubation
Tianhang Liu, Hechen Li, Long Bai +4
Robot-assisted airway intubation application needs high accuracy in locating targets and organs. Two vital landmarks, nostrils and glottis, can be detected during the intubation to…
Revisiting Distillation for Continual Learning on Visual Question Localized-Answering in Robotic Surgery
Long Bai, Mobarakol Islam, Hongliang Ren
The visual-question localized-answering (VQLA) system can serve as a knowledgeable assistant in surgical education. Except for providing text-based answers, the VQLA system can hig…
LLCaps: Learning to Illuminate Low-Light Capsule Endoscopy with Curved Wavelet Attention and Reverse Diffusion
Long Bai, Tong Chen, Yanan Wu +3
Wireless capsule endoscopy (WCE) is a painless and non-invasive diagnostic tool for gastrointestinal (GI) diseases. However, due to GI anatomical constraints and hardware manufactu…
SimCol3D -- 3D Reconstruction during Colonoscopy Challenge
Anita Rau, Sophia Bano, Yueming Jin +19
Colorectal cancer is one of the most common cancers in the world. While colonoscopy is an effective screening technique, navigating an endoscope through the colon to detect polyps…
Generalizing Surgical Instruments Segmentation to Unseen Domains with One-to-Many Synthesis
An Wang, Mobarakol Islam, Mengya Xu +1
Despite their impressive performance in various surgical scene understanding tasks, deep learning-based methods are frequently hindered from deploying to real-world surgical applic…
Curriculum-Based Augmented Fourier Domain Adaptation for Robust Medical Image Segmentation
An Wang, Mobarakol Islam, Mengya Xu +1
Accurate and robust medical image segmentation is fundamental and crucial for enhancing the autonomy of computer-aided diagnosis and intervention systems. Medical data collection n…
SME: Spatial-Spectral Mutual Teaching and Ensemble Learning for Scribble-supervised Polyp Segmentation
An Wang, Mengya Xu, Yang Zhang +2
Fully-supervised polyp segmentation has accomplished significant triumphs over the years in advancing the early diagnosis of colorectal cancer. However, label-efficient solutions f…
Surgical-VQLA: Transformer with Gated Vision-Language Embedding for Visual Question Localized-Answering in Robotic Surgery
Long Bai, Mobarakol Islam, Lalithkumar Seenivasan +1
Despite the availability of computer-aided simulators and recorded videos of surgical procedures, junior residents still heavily rely on experts to answer their queries. However, e…
Intuitive Surgical SurgToolLoc and SurgVU Challenges Results: 2022-2025
Aneeq Zia, Max Berniker, Rogerio Garcia Nespolo +153
Robotic assisted (RA) surgery promises to transform surgical intervention. Intuitive Surgical is committed to fostering these changes and the machine learning models and algorithms…
SAM Meets Robotic Surgery: An Empirical Study in Robustness Perspective
An Wang, Mobarakol Islam, Mengya Xu +2
Segment Anything Model (SAM) is a foundation model for semantic segmentation and shows excellent generalization capability with the prompts. In this empirical study, we investigate…
SurgicalGPT: End-to-End Language-Vision GPT for Visual Question Answering in Surgery
Lalithkumar Seenivasan, Mobarakol Islam, Gokul Kannan +1
Advances in GPT-based large language models (LLMs) are revolutionizing natural language processing, exponentially increasing its use across various domains. Incorporating uni-direc…
Paced-Curriculum Distillation with Prediction and Label Uncertainty for Image Segmentation
Mobarakol Islam, Lalithkumar Seenivasan, S. P. Sharan +4
Purpose: In curriculum learning, the idea is to train on easier samples first and gradually increase the difficulty, while in self-paced learning, a pacing function defines the spe…