7 papers
Explainable Anatomical Shape Analysis through Deep Hierarchical Generative Models
Carlo Biffi, Juan J. Cerrolaza, Giacomo Tarroni +12
Quantification of anatomical shape changes currently relies on scalar global indexes which are largely insensitive to regional or asymmetric modifications. Accurate assessment of p…
3D High-Resolution Cardiac Segmentation Reconstruction from 2D Views using Conditional Variational Autoencoders
Carlo Biffi, Juan J. Cerrolaza, Giacomo Tarroni +4
Accurate segmentation of heart structures imaged by cardiac MR is key for the quantitative analysis of pathology. High-resolution 3D MR sequences enable whole-heart structural imag…
Computational Anatomy for Multi-Organ Analysis in Medical Imaging: A Review
Juan J. Cerrolaza, Mirella Lopez-Picazo, Ludovic Humbert +4
The medical image analysis field has traditionally been focused on the development of organ-, and disease-specific methods. Recently, the interest in the development of more 20 com…
Small Organ Segmentation in Whole-body MRI using a Two-stage FCN and Weighting Schemes
Vanya V. Valindria, Ioannis Lavdas, Juan Cerrolaza +4
Accurate and robust segmentation of small organs in whole-body MRI is difficult due to anatomical variation and class imbalance. Recent deep network based approaches have demonstra…
A Generic Approach to Lung Field Segmentation from Chest Radiographs using Deep Space and Shape Learning
Awais Mansoor, Juan J. Cerrolaza, Geovanny Perez +4
Computer-aided diagnosis (CAD) techniques for lung field segmentation from chest radiographs (CXR) have been proposed for adult cohorts, but rarely for pediatric subjects. Statisti…
Standard Plane Detection in 3D Fetal Ultrasound Using an Iterative Transformation Network
Yuanwei Li, Bishesh Khanal, Benjamin Hou +8
Standard scan plane detection in fetal brain ultrasound (US) forms a crucial step in the assessment of fetal development. In clinical settings, this is done by manually manoeuvring…