Mohammad Yaqub
Orcid: 0000-0001-6896-1105
According to our database1,
Mohammad Yaqub
authored at least 94 papers
between 2011 and 2024.
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Bibliography
2024
CoNIC Challenge: Pushing the frontiers of nuclear detection, segmentation, classification and counting.
Medical Image Anal., February, 2024
Y-CA-Net: A Convolutional Attention Based Network for Volumetric Medical Image Segmentation.
CoRR, 2024
A Federated Learning-Friendly Approach for Parameter-Efficient Fine-Tuning of SAM in 3D Segmentation.
CoRR, 2024
CoRR, 2024
Continual Learning in Medical Imaging from Theory to Practice: A Survey and Practical Analysis.
CoRR, 2024
EDUE: Expert Disagreement-Guided One-Pass Uncertainty Estimation for Medical Image Segmentation.
CoRR, 2024
CoRR, 2024
Advanced Tumor Segmentation in Medical Imaging: An Ensemble Approach for BraTS 2023 Adult Glioma and Pediatric Tumor Tasks.
CoRR, 2024
XReal: Realistic Anatomy and Pathology-Aware X-ray Generation via Controllable Diffusion Model.
CoRR, 2024
CoRR, 2024
Corrections to "RespiroDynamics: A Multifaceted Dataset for Enhanced Lung Health Assessment Using Deep Learning".
IEEE Access, 2024
RespiroDynamics: A Multifaceted Dataset for Enhanced Lung Health Assessment Using Deep Learning.
IEEE Access, 2024
iML at SemEval-2024 Task 2: Safe Biomedical Natural Language Interference for Clinical Trials with LLM Based Ensemble Inferencing.
Proceedings of the 18th International Workshop on Semantic Evaluation, 2024
DynaMMo: Dynamic Model Merging for Efficient Class Incremental Learning for Medical Images.
Proceedings of the Medical Image Understanding and Analysis - 28th Annual Conference, 2024
FissionFusion: Fast Geometric Generation and Hierarchical Souping for Medical Image Analysis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024
TiBiX: Leveraging Temporal Information for Bidirectional X-Ray and Report Generation.
Proceedings of the Deep Generative Models - 4th MICCAI Workshop, 2024
SurvRNC: Learning Ordered Representations for Survival Prediction Using Rank-N-Contrast.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024
Proceedings of the Cancer Prevention, Detection, and Intervention - Third MICCAI Workshop, 2024
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024
GUARDIAN: Guarding Against Uncertainty and Adversarial Risks in Robot-Assisted Surgeries.
Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, 2024
Dynamic Dashboard for Malaria Control: Integrating Climate Factors for Comprehensive Monitoring.
Proceedings of the IEEE International Symposium on Medical Measurements and Applications, 2024
On Enhancing Brain Tumor Segmentation across Diverse Populations with Convolutional Neural Networks.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024
Envisioning Medclip: A Deep Dive into Explainability for Medical Vision-Language Models.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024
2023
MGMT promoter methylation status prediction using MRI scans? An extensive experimental evaluation of deep learning models.
Medical Image Anal., December, 2023
Machine learning for accurate estimation of fetal gestational age based on ultrasound images.
npj Digit. Medicine, 2023
FUSC: Fetal Ultrasound Semantic Clustering of Second Trimester Scans Using Deep Self-supervised Learning.
CoRR, 2023
UniLVSeg: Unified Left Ventricular Segmentation with Sparsely Annotated Echocardiogram Videos through Self-Supervised Temporal Masking and Weakly Supervised Training.
CoRR, 2023
Prompt-based Tuning of Transformer Models for Multi-Center Medical Image Segmentation.
CoRR, 2023
Surgical tool classification and localization: results and methods from the MICCAI 2022 SurgToolLoc challenge.
CoRR, 2023
CoRR, 2023
CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting.
CoRR, 2023
In Quest of Ground Truth: Learning Confident Models and Estimating Uncertainty in the Presence of Annotator Noise.
CoRR, 2023
PECon: Contrastive Pretraining to Enhance Feature Alignment Between CT and EHR Data for Improved Pulmonary Embolism Diagnosis.
Proceedings of the Machine Learning in Medical Imaging - 14th International Workshop, 2023
Proceedings of the Medical Image Understanding and Analysis - 27th Annual Conference, 2023
Proceedings of the Medical Imaging with Deep Learning, 2023
DGM-DR: Domain Generalization with Mutual Information Regularized Diabetic Retinopathy Classification.
Proceedings of the Domain Adaptation and Representation Transfer - 5th MICCAI Workshop, 2023
SEDA: Self-ensembling ViT with Defensive Distillation and Adversarial Training for Robust Chest X-Rays Classification.
Proceedings of the Domain Adaptation and Representation Transfer - 5th MICCAI Workshop, 2023
Proceedings of the Applications of Medical Artificial Intelligence, 2023
Leveraging Self-supervised Learning for Fetal Cardiac Planes Classification Using Ultrasound Scan Videos.
Proceedings of the Simplifying Medical Ultrasound - 4th International Workshop, 2023
Multi-task Learning Approach for Unified Biometric Estimation from Fetal Ultrasound Anomaly Scans.
Proceedings of 2023 International Conference on Medical Imaging and Computer-Aided Diagnosis, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
2022
A Radiogenomics Pipeline for Lung Nodules Segmentation and Prediction of EGFR Mutation Status from CT Scans.
CoRR, 2022
CoRR, 2022
CoRR, 2022
CoRR, 2022
SubOmiEmbed: Self-supervised Representation Learning of Multi-omics Data for Cancer Type Classification.
CoRR, 2022
Is Contrastive Learning Suitable for Left Ventricular Segmentation in Echocardiographic Images?
CoRR, 2022
Deep Learning-based Quality Assessment of Clinical Protocol Adherence in Fetal Ultrasound Dating Scans.
CoRR, 2022
Challenges in COVID-19 Chest X-Ray Classification: Problematic Data or Ineffective Approaches?
CoRR, 2022
IEEE Access, 2022
Proceedings of the Medical Image Understanding and Analysis - 26th Annual Conference, 2022
Self-supervision and Multi-task Learning: Challenges in Fine-Grained COVID-19 Multi-class Classification from Chest X-rays.
Proceedings of the Medical Image Understanding and Analysis - 26th Annual Conference, 2022
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022
Is it Possible to Predict MGMT Promoter Methylation from Brain Tumor MRI Scans using Deep Learning Models?
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022
Proceedings of the Simplifying Medical Ultrasound - Third International Workshop, 2022
TMSS: An End-to-End Transformer-Based Multimodal Network for Segmentation and Survival Prediction.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
EchoCoTr: Estimation of the Left Ventricular Ejection Fraction from Spatiotemporal Echocardiography.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
GARDNet: Robust Multi-view Network for Glaucoma Classification in Color Fundus Images.
Proceedings of the Ophthalmic Medical Image Analysis - 9th International Workshop, 2022
Proceedings of the Simplifying Medical Ultrasound - Third International Workshop, 2022
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2022
TransResNet: Integrating the Strengths of ViTs and CNNs for High Resolution Medical Image Segmentation via Feature Grafting.
Proceedings of the 33rd British Machine Vision Conference 2022, 2022
Proceedings of the 33rd British Machine Vision Conference 2022, 2022
Proceedings of the 33rd British Machine Vision Conference 2022, 2022
2021
Continual Domain Incremental Learning for Chest X-Ray Classification in Low-Resource Clinical Settings.
Proceedings of the Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health, 2021
An Ensemble Approach for Patient Prognosis of Head and Neck Tumor Using Multimodal Data.
Proceedings of the Head and Neck Tumor Segmentation and Outcome Prediction, 2021
Proceedings of the Simplifying Medical Ultrasound - Second International Workshop, 2021
2020
A High-Resolution Global Map of Giant Kelp (Macrocystis pyrifera) Forests and Intertidal Green Algae (Ulvophyceae) with Sentinel-2 Imagery.
Remote. Sens., 2020
Proceedings of the Medical Ultrasound, and Preterm, Perinatal and Paediatric Image Analysis, 2020
2018
Fully-automated alignment of 3D fetal brain ultrasound to a canonical reference space using multi-task learning.
Medical Image Anal., 2018
IET Comput. Vis., 2018
2016
Plane Localization in 3-D Fetal Neurosonography for Longitudinal Analysis of the Developing Brain.
IEEE J. Biomed. Health Informatics, 2016
Automated 3D Ultrasound Biometry Planes Extraction for First Trimester Fetal Assessment.
Proceedings of the Machine Learning in Medical Imaging - 7th International Workshop, 2016
2015
Learning-based prediction of gestational age from ultrasound images of the fetal brain.
Medical Image Anal., 2015
Automated Mid-sagittal Plane Selection for Corpus Callosum Visualization in 3D Ultrasound Images.
Proceedings of the Medical Image Understanding and Analysis, 2015
Guided Random Forests for Identification of Key Fetal Anatomy and Image Categorization in Ultrasound Scans.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference Munich, Germany, October 5, 2015
2014
Investigation of the Role of Feature Selection and Weighted Voting in Random Forests for 3-D Volumetric Segmentation.
IEEE Trans. Medical Imaging, 2014
Evaluation and Comparison of Current Fetal Ultrasound Image Segmentation Methods for Biometric Measurements: A Grand Challenge.
IEEE Trans. Medical Imaging, 2014
A Constrained Regression Forests Solution to 3D Fetal Ultrasound Plane Localization for Longitudinal Analysis of Brain Growth and Maturation.
Proceedings of the Machine Learning in Medical Imaging - 5th International Workshop, 2014
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2014, 2014
2013
Proceedings of the Machine Learning in Medical Imaging - 4th International Workshop, 2013
Class-Specific Regression Random Forest for Accurate Extraction of Standard Planes from 3D Echocardiography.
Proceedings of the Medical Computer Vision. Large Data in Medical Imaging, 2013
Proceedings of the 10th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2013
2012
Novel Context Rich LoCo and GloCo Features with Local and Global Shape Constraints for Segmentation of 3D Echocardiograms with Random Forests.
Proceedings of the Medical Computer Vision. Recognition Techniques and Applications in Medical Imaging, 2012
Proceedings of the 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2012
2011
Improving the Classification Accuracy of the Classic RF Method by Intelligent Feature Selection and Weighted Voting of Trees with Application to Medical Image Segmentation.
Proceedings of the Machine Learning in Medical Imaging - Second International Workshop, 2011
Learning Optical Flow Propagation Strategies Using Random Forests for Fast Segmentation in Dynamic 2D & 3D Echocardiography.
Proceedings of the Machine Learning in Medical Imaging - Second International Workshop, 2011