4 citations · 11 across the 14 of their papers we have counts for
15 papers
DuPLUS: Dual-Prompt Vision-Language Framework for Universal Medical Image Segmentation and Prognosis
Numan Saeed, Tausifa Jan Saleem, Fadillah Maani +3
Deep learning for medical imaging is hampered by task-specific models that lack generalizability and prognostic capabilities, while existing 'universal' approaches suffer from simp…
A Multimodal and Multi-centric Head and Neck Cancer Dataset for Segmentation, Diagnosis and Outcome Prediction
Numan Saeed, Salma Hassan, Shahad Hardan +40
We present a publicly available multimodal dataset for head and neck cancer research, comprising 1123 annotated Positron Emission Tomography/Computed Tomography (PET/CT) studies fr…
Efficient Parameter Adaptation for Multi-Modal Medical Image Segmentation and Prognosis
Numan Saeed, Shahad Hardan, Muhammad Ridzuan +3
Cancer detection and prognosis relies heavily on medical imaging, particularly CT and PET scans. Deep Neural Networks (DNNs) have shown promise in tumor segmentation by fusing info…
Breaking Down the Hierarchy: A New Approach to Leukemia Classification
Ibraheem Hamdi, Hosam El-Gendy, Ahmed Sharshar +8
The complexities inherent to leukemia, multifaceted cancer affecting white blood cells, pose considerable diagnostic and treatment challenges, primarily due to reliance on laboriou…
SurvCORN: Survival Analysis with Conditional Ordinal Ranking Neural Network
Muhammad Ridzuan, Numan Saeed, Fadillah Adamsyah Maani +2
Survival analysis plays a crucial role in estimating the likelihood of future events for patients by modeling time-to-event data, particularly in healthcare settings where predicti…
SurvRNC: Learning Ordered Representations for Survival Prediction using Rank-N-Contrast
Numan Saeed, Muhammad Ridzuan, Fadillah Adamsyah Maani +3
Predicting the likelihood of survival is of paramount importance for individuals diagnosed with cancer as it provides invaluable information regarding prognosis at an early stage.…
HuLP: Human-in-the-Loop for Prognosis
Muhammad Ridzuan, Mai Kassem, Numan Saeed +2
This paper introduces HuLP, a Human-in-the-Loop for Prognosis model designed to enhance the reliability and interpretability of prognostic models in clinical contexts, especially w…
DGM-DR: Domain Generalization with Mutual Information Regularized Diabetic Retinopathy Classification
Aleksandr Matsun, Dana O. Mohamed, Sharon Chokuwa +2
The domain shift between training and testing data presents a significant challenge for training generalizable deep learning models. As a consequence, the performance of models tra…
Prompt-Based Tuning of Transformer Models for Multi-Center Medical Image Segmentation of Head and Neck Cancer
Numan Saeed, Muhammad Ridzuan, Roba Al Majzoub +1
Medical image segmentation is a vital healthcare endeavor requiring precise and efficient models for appropriate diagnosis and treatment. Vision transformer (ViT)-based segmentatio…
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…
CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting
Simon Graham, Quoc Dang Vu, Mostafa Jahanifar +86
Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome. To drive innovatio…
Color Space-based HoVer-Net for Nuclei Instance Segmentation and Classification
Hussam Azzuni, Muhammad Ridzuan, Min Xu +1
Nuclei segmentation and classification is the first and most crucial step that is utilized for many different microscopy medical analysis applications. However, it suffers from man…
Hyperparameter Optimization for COVID-19 Chest X-Ray Classification
Ibraheem Hamdi, Muhammad Ridzuan, Mohammad Yaqub
Despite the introduction of vaccines, Coronavirus disease (COVID-19) remains a worldwide dilemma, continuously developing new variants such as Delta and the recent Omicron. The cur…
Self-Supervision and Multi-Task Learning: Challenges in Fine-Grained COVID-19 Multi-Class Classification from Chest X-rays
Muhammad Ridzuan, Ameera Ali Bawazir, Ivo Gollini Navarette +2
Quick and accurate diagnosis is of paramount importance to mitigate the effects of COVID-19 infection, particularly for severe cases. Enormous effort has been put towards developin…
Self-Supervised Learning for Fine-Grained Image Classification
Farha Al Breiki, Muhammad Ridzuan, Rushali Grandhe
Fine-grained image classification involves identifying different subcategories of a class which possess very subtle discriminatory features. Fine-grained datasets usually provide b…