Area of research
Radiology, Nuclear Medicine and Imaging · Computer Vision and Pattern Recognition
Research interest
Research interests include Medical Image Segmentation Techniques, Advanced MRI Techniques and Applications, Medical Imaging Techniques and Applications, and Radiomics and Machine Learning in Medical Imaging.
Development of an Automated Tool for the Estimation of Histological Remission in Ulcerative Colitis Using Single-Wavelength Endoscopy Technology.
Automated quantification of lung pathology on micro-CT in diverse disease models using deep learning.
Real-time automated assessment of histological disease activity in patients with ulcerative colitis using single-wavelength endoscopy technology.
Automated Classification of Neuromuscular Diseases Using Thigh Muscle MRI With Model Interpretations
395PAdvancing clinical trials in myotonic dystrophy type 1: refining radiological, clinical and patient-reported outcome measures
408PNatural disease progression in adult CMT1A: a prospective study using quantitative MRI and clinical assessments
Automated Classification of Neuromuscular Diseases Using Thigh Muscle MRI With Model Interpretations.
Local response function estimation in spherical deconvolution for comprehensive tissue representation using diffusion MRI.
Clinical consequences of computer-aided colorectal polyp detection.
Lessons for future clinical trials in adults with Becker muscular dystrophy: Disease progression detected by muscle magnetic resonance imaging, clinical and patient‐reported outcome measures
Automated biventricular quantification in patients with repaired tetralogy of Fallot using a three-dimensional deep learning segmentation model.
Deep learning pipeline for quality filtering of MRSI spectra.
Lessons for future clinical trials in adults with Becker muscular dystrophy: Disease progression detected by muscle magnetic resonance imaging, clinical and patient-reported outcome measures.
Test-retest reliability and follow-up of muscle magnetic resonance elastography in adults with and without muscle diseases.
Segmentation-based quantitative measurements in renal CT imaging using deep learning.
Deep Learning Approaches for Automated Classification of Muscular Dystrophies from MRI
Deep Learning Approaches for Automated Classification of Muscular Dystrophies from MRI
Benefits of automated gross tumor volume segmentation in head and neck cancer using multi-modality information
Benefits of automated gross tumor volume segmentation in head and neck cancer using multi-modality information.
Automated MRI quantification of volumetric per-muscle fat fractions in the proximal leg of patients with muscular dystrophies.
Histopathological correlations and fat replacement imaging patterns in recessive limb‐girdle muscular dystrophy type 12
Factorizer: A scalable interpretable approach to context modeling for medical image segmentation.
Advanced Imaging in Gastrointestinal Endoscopy: A Literature Review of the Current State of the Art.
Histopathological correlations and fat replacement imaging patterns in recessive limb-girdle muscular dystrophy type 12.
Deep learning based MLC aperture and monitor unit prediction as a warm start for breast VMAT optimisation.
P252 Exploration of muscle MR imaging and clinical outcome measures in adults with Becker muscular dystrophy
Artificial Intelligence Based Patient-Specific Preoperative Planning Algorithm for Total Knee Arthroplasty
Factorizer: A scalable interpretable approach to context modeling for medical image segmentation
Artificial Intelligence Based Patient-Specific Preoperative Planning Algorithm for Total Knee Arthroplasty.
Clinical evaluation of a deep learning model for segmentation of target volumes in breast cancer radiotherapy