8 citations · 12 across the 12 of their papers we have counts for
6 papers · 1 filter
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…
FetalCLIP: A Visual-Language Foundation Model for Fetal Ultrasound Image Analysis
Fadillah Maani, Numan Saeed, Tausifa Saleem +8
Foundation models are becoming increasingly effective in the medical domain, offering pre-trained models on large datasets that can be readily adapted for downstream tasks. Despite…
Leveraging Self-Supervised Learning for Fetal Cardiac Planes Classification using Ultrasound Scan Videos
Joseph Geo Benjamin, Mothilal Asokan, Amna Alhosani +5
Self-supervised learning (SSL) methods are popular since they can address situations with limited annotated data by directly utilising the underlying data distribution. However, th…
MGMT promoter methylation status prediction using MRI scans? An extensive experimental evaluation of deep learning models
Numan Saeed, Muhammad Ridzuan, Hussain Alasmawi +2
The number of studies on deep learning for medical diagnosis is expanding, and these systems are often claimed to outperform clinicians. However, only a few systems have shown medi…
Weakly Unsupervised Domain Adaptation for Vestibular Schwannoma Segmentation
Shahad Hardan, Hussain Alasmawi, Xiangjian Hou +1
Vestibular schwannoma (VS) is a non-cancerous tumor located next to the ear that can cause hearing loss. Most brain MRI images acquired from patients are contrast-enhanced T1 (ceT1…
Automatic Segmentation of Head and Neck Tumor: How Powerful Transformers Are?
Ikboljon Sobirov, Otabek Nazarov, Hussain Alasmawi +1
Cancer is one of the leading causes of death worldwide, and head and neck (H&N) cancer is amongst the most prevalent types. Positron emission tomography and computed tomography are…