103 citations · 349 across the 55 of their papers we have counts for
18 papers · 1 filter
Transferring Knowledge from High-Quality to Low-Quality MRI for Adult Glioma Diagnosis
Yanguang Zhao, Long Bai, Zhaoxi Zhang +3
Glioma, a common and deadly brain tumor, requires early diagnosis for improved prognosis. However, low-quality Magnetic Resonance Imaging (MRI) technology in Sub-Saharan Africa (SS…
EndoUIC: Promptable Diffusion Transformer for Unified Illumination Correction in Capsule Endoscopy
Long Bai, Tong Chen, Qiaozhi Tan +10
Wireless Capsule Endoscopy (WCE) is highly valued for its non-invasive and painless approach, though its effectiveness is compromised by uneven illumination from hardware constrain…
EndoDAC: Efficient Adapting Foundation Model for Self-Supervised Depth Estimation from Any Endoscopic Camera
Beilei Cui, Mobarakol Islam, Long Bai +2
Depth estimation plays a crucial role in various tasks within endoscopic surgery, including navigation, surface reconstruction, and augmented reality visualization. Despite the sig…
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…
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…
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…
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…
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…
Class Balanced PixelNet for Neurological Image Segmentation
Mobarakol Islam, Hongliang Ren
In this paper, we propose an automatic brain tumor segmentation approach (e.g., PixelNet) using a pixel-level convolutional neural network (CNN). The model extracts feature from mu…
Ischemic Stroke Lesion Segmentation Using Adversarial Learning
Mobarakol Islam, N Rajiv Vaidyanathan, V Jeya Maria Jose +1
Ischemic stroke occurs through a blockage of clogged blood vessels supplying blood to the brain. Segmentation of the stroke lesion is vital to improve diagnosis, outcome assessment…
Global-Reasoned Multi-Task Learning Model for Surgical Scene Understanding
Lalithkumar Seenivasan, Sai Mitheran, Mobarakol Islam +1
Global and local relational reasoning enable scene understanding models to perform human-like scene analysis and understanding. Scene understanding enables better semantic segmenta…
2020 CATARACTS Semantic Segmentation Challenge
Imanol Luengo, Maria Grammatikopoulou, Rahim Mohammadi +37
Surgical scene segmentation is essential for anatomy and instrument localization which can be further used to assess tissue-instrument interactions during a surgical procedure. In…
Glioblastoma Multiforme Prognosis: MRI Missing Modality Generation, Segmentation and Radiogenomic Survival Prediction
Mobarakol Islam, Navodini Wijethilake, Hongliang Ren
The accurate prognosis of Glioblastoma Multiforme (GBM) plays an essential role in planning correlated surgeries and treatments. The conventional models of survival prediction rely…
Brain Tumor Segmentation and Survival Prediction using 3D Attention UNet
Mobarakol Islam, Vibashan VS, V Jeya Maria Jose +3
In this work, we develop an attention convolutional neural network (CNN) to segment brain tumors from Magnetic Resonance Images (MRI). Further, we predict the survival rate using v…
Glioma Prognosis: Segmentation of the Tumor and Survival Prediction using Shape, Geometric and Clinical Information
Mobarakol Islam, V Jeya Maria Jose, Hongliang Ren
Segmentation of brain tumor from magnetic resonance imaging (MRI) is a vital process to improve diagnosis, treatment planning and to study the difference between subjects with tumo…