3 citations · 9 across the 10 of their papers we have counts for
10 papers
crossMoDA Challenge: Evolution of Cross-Modality Domain Adaptation Techniques for Vestibular Schwannoma and Cochlea Segmentation from 2021 to 2023
Navodini Wijethilake, Reuben Dorent, Marina Ivory +38
The cross-Modality Domain Adaptation (crossMoDA) challenge series, initiated in 2021 in conjunction with the International Conference on Medical Image Computing and Computer Assist…
All Languages Matter: Evaluating LMMs on Culturally Diverse 100 Languages
Ashmal Vayani, Dinura Dissanayake, Hasindri Watawana +66
Existing Large Multimodal Models (LMMs) generally focus on only a few regions and languages. As LMMs continue to improve, it is increasingly important to ensure they understand cul…
Continual Learning in Medical Imaging: A Survey and Practical Analysis
Mohammad Areeb Qazi, Anees Ur Rehman Hashmi, Santosh Sanjeev +4
Deep Learning has shown great success in reshaping medical imaging, yet it faces numerous challenges hindering widespread application. Issues like catastrophic forgetting and distr…
DynaMMo: Dynamic Model Merging for Efficient Class Incremental Learning for Medical Images
Mohammad Areeb Qazi, Ibrahim Almakky, Anees Ur Rehman Hashmi +2
Continual learning, the ability to acquire knowledge from new data while retaining previously learned information, is a fundamental challenge in machine learning. Various approache…
TiBiX: Leveraging Temporal Information for Bidirectional X-ray and Report Generation
Santosh Sanjeev, Fadillah Adamsyah Maani, Arsen Abzhanov +4
With the emergence of vision language models in the medical imaging domain, numerous studies have focused on two dominant research activities: (1) report generation from Chest X-ra…
FissionFusion: Fast Geometric Generation and Hierarchical Souping for Medical Image Analysis
Santosh Sanjeev, Nuren Zhaksylyk, Ibrahim Almakky +3
The scarcity of well-annotated medical datasets requires leveraging transfer learning from broader datasets like ImageNet or pre-trained models like CLIP. Model soups averages mult…
MedMerge: Merging Models for Effective Transfer Learning to Medical Imaging Tasks
Ibrahim Almakky, Santosh Sanjeev, Anees Ur Rehman Hashmi +3
Transfer learning has become a powerful tool to initialize deep learning models to achieve faster convergence and higher performance. This is especially useful in the medical imagi…
XReal: Realistic Anatomy and Pathology-Aware X-ray Generation via Controllable Diffusion Model
Anees Ur Rehman Hashmi, Ibrahim Almakky, Mohammad Areeb Qazi +4
Large-scale generative models have demonstrated impressive capabilities in producing visually compelling images, with increasing applications in medical imaging. However, they cont…
Exploring the Transfer Learning Capabilities of CLIP in Domain Generalization for Diabetic Retinopathy
Sanoojan Baliah, Fadillah A. Maani, Santosh Sanjeev +1
Diabetic Retinopathy (DR), a leading cause of vision impairment, requires early detection and treatment. Developing robust AI models for DR classification holds substantial potenti…
PECon: Contrastive Pretraining to Enhance Feature Alignment between CT and EHR Data for Improved Pulmonary Embolism Diagnosis
Santosh Sanjeev, Salwa K. Al Khatib, Mai A. Shaaban +3
Previous deep learning efforts have focused on improving the performance of Pulmonary Embolism(PE) diagnosis from Computed Tomography (CT) scans using Convolutional Neural Networks…