1 citations · 1 across the 3 of their papers we have counts for
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EDUE: Expert Disagreement-Guided One-Pass Uncertainty Estimation for Medical Image Segmentation
Kudaibergen Abutalip, Numan Saeed, Ikboljon Sobirov +3
Deploying deep learning (DL) models in medical applications relies on predictive performance and other critical factors, such as conveying trustworthy predictive uncertainty. Uncer…
Advanced Tumor Segmentation in Medical Imaging: An Ensemble Approach for BraTS 2023 Adult Glioma and Pediatric Tumor Tasks
Fadillah Maani, Anees Ur Rehman Hashmi, Mariam Aljuboory +3
Automated segmentation proves to be a valuable tool in precisely detecting tumors within medical images. The accurate identification and segmentation of tumor types hold paramount…
Structurally Different Neural Network Blocks for the Segmentation of Atrial and Aortic Perivascular Adipose Tissue in Multi-centre CT Angiography Scans
Ikboljon Sobirov, Cheng Xie, Muhammad Siddique +26
Since the emergence of convolutional neural networks (CNNs) and, later, vision transformers (ViTs), deep learning architectures have predominantly relied on identical block types w…
Diagnosis and Prognosis of Head and Neck Cancer Patients using Artificial Intelligence
Ikboljon Sobirov
Cancer is one of the most life-threatening diseases worldwide, and head and neck (H&N) cancer is a prevalent type with hundreds of thousands of new cases recorded each year. Clinic…
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…
TMSS: An End-to-End Transformer-based Multimodal Network for Segmentation and Survival Prediction
Numan Saeed, Ikboljon Sobirov, Roba Al Majzoub +1
When oncologists estimate cancer patient survival, they rely on multimodal data. Even though some multimodal deep learning methods have been proposed in the literature, the majorit…