39 citations · 91 across the 33 of their papers we have counts for
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On the Importance of Image Encoding in Automated Chest X-Ray Report Generation
Otabek Nazarov, Mohammad Yaqub, Karthik Nandakumar
Chest X-ray is one of the most popular medical imaging modalities due to its accessibility and effectiveness. However, there is a chronic shortage of well-trained radiologists who…
A Radiogenomics Pipeline for Lung Nodules Segmentation and Prediction of EGFR Mutation Status from CT Scans
Ivo Gollini Navarrete, Mohammad Yaqub
Lung cancer is a leading cause of death worldwide. Early-stage detection of lung cancer is essential for a more favorable prognosis. Radiogenomics is an emerging discipline that co…
How to Train Vision Transformer on Small-scale Datasets?
Hanan Gani, Muzammal Naseer, Mohammad Yaqub
Vision Transformer (ViT), a radically different architecture than convolutional neural networks offers multiple advantages including design simplicity, robustness and state-of-the-…
Self-omics: A Self-supervised Learning Framework for Multi-omics Cancer Data
Sayed Hashim, Karthik Nandakumar, Mohammad Yaqub
We have gained access to vast amounts of multi-omics data thanks to Next Generation Sequencing. However, it is challenging to analyse this data due to its high dimensionality and m…
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…
EchoCoTr: Estimation of the Left Ventricular Ejection Fraction from Spatiotemporal Echocardiography
Rand Muhtaseb, Mohammad Yaqub
Learning spatiotemporal features is an important task for efficient video understanding especially in medical images such as echocardiograms. Convolutional neural networks (CNNs) a…
Self-Ensembling Vision Transformer (SEViT) for Robust Medical Image Classification
Faris Almalik, Mohammad Yaqub, Karthik Nandakumar
Vision Transformers (ViT) are competing to replace Convolutional Neural Networks (CNN) for various computer vision tasks in medical imaging such as classification and segmentation.…
GARDNet: Robust Multi-View Network for Glaucoma Classification in Color Fundus Images
Ahmed Al Mahrooqi, Dmitrii Medvedev, Rand Muhtaseb +1
Glaucoma is one of the most severe eye diseases, characterized by rapid progression and leading to irreversible blindness. It is often the case that diagnostics is carried out when…
Super Images -- A New 2D Perspective on 3D Medical Imaging Analysis
Ikboljon Sobirov, Numan Saeed, Mohammad Yaqub
In medical imaging analysis, deep learning has shown promising results. We frequently rely on volumetric data to segment medical images, necessitating the use of 3D architectures,…
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…
Is it Possible to Predict MGMT Promoter Methylation from Brain Tumor MRI Scans using Deep Learning Models?
Numan Saeed, Shahad Hardan, Kudaibergen Abutalip +1
Glioblastoma is a common brain malignancy that tends to occur in older adults and is almost always lethal. The effectiveness of chemotherapy, being the standard treatment for most…
An Ensemble Approach for Patient Prognosis of Head and Neck Tumor Using Multimodal Data
Numan Saeed, Roba Al Majzoub, Ikboljon Sobirov +1
Accurate prognosis of a tumor can help doctors provide a proper course of treatment and, therefore, save the lives of many. Traditional machine learning algorithms have been eminen…
SubOmiEmbed: Self-supervised Representation Learning of Multi-omics Data for Cancer Type Classification
Sayed Hashim, Muhammad Ali, Karthik Nandakumar +1
For personalized medicines, very crucial intrinsic information is present in high dimensional omics data which is difficult to capture due to the large number of molecular features…
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…
Deep Learning-based Quality Assessment of Clinical Protocol Adherence in Fetal Ultrasound Dating Scans
Sevim Cengiz, Mohammad Yaqub
To assess fetal health during pregnancy, doctors use the gestational age (GA) calculation based on the Crown Rump Length (CRL) measurement in order to check for fetal size and grow…
Contrastive Pretraining for Echocardiography Segmentation with Limited Data
Mohamed Saeed, Rand Muhtaseb, Mohammad Yaqub
Contrastive learning has proven useful in many applications where access to labelled data is limited. The lack of annotated data is particularly problematic in medical image segmen…
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…
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…