2021
Dr. Hassan joins the Editorial Board of Artificial Intelligence in Radiology in Frontiers in Radiology.
Paper accepted at the BrainLesion Workshop, MICCAI Conference, 2021: E1D3 U-Net for Brain Tumor Segmentation: Submission to the RSNA-ASNR-MICCAI BraTS 2021 Challenge.
Paper accepted at the M&Ms-2 Challenge, MICCAI Conference, 2021: Multi-view SA-LA Net: A framework for simultaneous segmentation of RV on multi-view cardiac MR Images.
Dr. Hassan is an invited speaker at the Big Data in Biomedicine Seminar Series, Precision Medicine Lab. The title of the talk is Brain Tumor Characterization with Radiogenomics and Deep Learning.
Dr. Hassan is a guest speaker at King Edward Medical University Lahore / Mayo Hospital Lahore. He will speak on the topic of Artificial Intelligence and Medical Imaging.
Paper published in the Multimedia Tools and Applications: Two-stage active contour model for robust left ventricle segmentation in cardiac MRI.
Paper published in the Physics in Medicine and Biology: A systematic evaluation of learning rate policies in training CNNs for brain tumor segmentation.
Paper published as part of RNO-AI 2020 workshop organized by MICCAI 2020: Overall Survival Prediction in Gliomas Using Region-Specific Radiomic Features.
Our book on Radiomics and Radiogenomics in Neuro-oncology is now available. It is published as part of the Lecture Notes in Computer Science by Springer. We thank the entire team of RNO-AI 2020 and the authors who contributed to the articles.
2020
RNO-AI 2020 workshop has been accepted at MICCAI 2020. RNO-AI 2020 is a comprehensive MICCAI workshop on Radiomics and Radiogenomics in Neuro-oncology using AI. [Workshop Website]
Our book on Radiomics and Radiogenomics in Neuro-oncology is now available. It is published as part of the Lecture Notes in Computer Science by Springer. We thank the entire team of RNO-AI 2019 and the authors who contributed to the articles.
2019
Dr. Hassan is a recipient of 2019 Public Health Research Grant from the Shahid Hussain Foundation.
Dr. Hassan is a recipient of 2019 Charles Wallace Fellowship from the British Council of Pakistan. [News Feed]
RNO-AI 2019 workshop has been accepted at MICCAI 2019. RNO-AI 2019 is the first comprehensive MICCAI workshop on Radiomics and Radiogenomics in Neuro-oncology using AI. [Workshop Website]
2018
LUMS coverage of Clinical and Translational Imaging Lab. [News Feed]
2018 Faculty Initiative Fund for a project on Hepatocellular Carcinoma.
Clinical and Translational Imaging Lab launched at LUMS. [Website]
Research grant (PKR 20 million) awarded by the Higher Education Commission and Planning Commission of Pakistan to establish a lab on Clinical and Translational Imagingat the Syed Babar Ali School of Science and Engineering, LUMS. The lab will be housed under the National Centre for Big Data and Cloud Computing at LUMS. [News Feed]
Start-up grant (PKR 1.6 million) awarded by Syed Babar Ali School of Science and Engineering, LUMS for research in medical imaging.
2017
Paper in Computer Methods and Programs in Biomedicine: Enhancement of dynamic myocardial perfusion PET images based on low-rank plus sparse decomposition.
Paper in Medical Physics journal: A novel blind deconvolution method incorporated with anatomical-based filtering for partial volume correction: validations with 123-I-mIBG cardiac SPECT/CT. [JNM Abstract]
Our paper has now been featured as a news article on medicalphysicsweb.
Editorial on my paper in the Journal of Nuclear Cardiology by Kieran S. Chung and Patricia K. Nguyen: Non- invasive measures of coronary microcirculation: Taking the long road to the clinic.
Paper in the Journal of Nuclear Cardiology: Quantification of intramyocardial blood volume with 99mTc-RBC SPECT-CT imaging: A preclinical study. [Slides]
Paper in Physics in Medicine and Biology: Generalized PSF modeling for optimized quantitation in PET Imaging.
Invited talk at the 5th PAK SNM Conference & 1st Sino-PAK Nuclear Medicine Symposium: Quantitative Multimodality Cardiac Imaging: Applications in Clinical and Translational Research.
Paper in Physics in Medicine and Biology: Fully automatic multi-atlas segmentation of CTA for partial volume correction in cardiac SPECT/CT.