BACKGROUND: Human cortical primary sulci are relatively stable landmarks and commonly observed across the population. Despite their stability, the primary sulci exhibit phenotypic variability.
Deep multitask learning for face analysis has received increasing attentions. From literature, most existing methods focus on optimizing a main task by jointly learning several auxiliary tasks. It is challenging to consider the performance of each ta...
Early detection and localization of prostate tumors pose a challenge to the medical community. Several imaging techniques, including PET, have shown some success. But no robust and accurate solution has yet been reached. This work aims to detect pros...
In many medical image analysis applications, only a limited amount of training data is available due to the costs of image acquisition and the large manual annotation effort required from experts. Training recent state-of-the-art machine learning met...
European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
Mar 12, 2019
PURPOSE: We present an automated method for extracting anatomical parameters from biplanar radiographs of the spine, which is able to deal with a wide scenario of conditions, including sagittal and coronal deformities, degenerative phenomena as well ...
This paper presents a new approach to automatic three-dimensional (3D) cephalometric annotation for diagnosis, surgical planning, and treatment evaluation. There has long been considerable demand for automated cephalometric landmarking, since manual ...
Automatic detection of anatomical landmarks is an important step for a wide range of applications in medical image analysis. Manual annotation of landmarks is a tedious task and prone to observer errors. In this paper, we evaluate novel deep reinforc...
In this paper, we propose a novel deep learning framework for anatomy segmentation and automatic landmarking. Specifically, we focus on the challenging problem of mandible segmentation from cone-beam computed tomography (CBCT) scans and identificatio...
IEEE transactions on bio-medical engineering
Sep 12, 2018
In the field of computer-aided Alzheimer's disease (AD) diagnosis, jointly identifying brain diseases and predicting clinical scores using magnetic resonance imaging (MRI) have attracted increasing attention since these two tasks are highly correlate...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Aug 25, 2018
We present a new method to identify anatomical subnetworks of the human connectome that are optimally predictive of targeted clinical variables, developmental outcomes or disease states. Given a training set of structural or functional brain networks...