AIMC Topic: Anatomic Landmarks
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Accurate and robust deep learning-based segmentation of the prostate clinical target volume in ultrasound images.
Medical image analysis
Jul 15, 2019
The goal of this work was to develop a method for accurate and robust automatic segmentation of the prostate clinical target volume in transrectal ultrasound (TRUS) images for brachytherapy. These images can be difficult to segment because of weak or...
MAPGI: Accurate identification of anatomical landmarks and diseased tissue in gastrointestinal tract using deep learning.
Computers in biology and medicine
Jul 10, 2019
Automatic detection of anatomical landmarks and diseases in medical images is a challenging task which could greatly aid medical diagnosis and reduce the cost and time of investigational procedures. Also, two particular challenges of digital image pr...
Breast pectoral muscle segmentation in mammograms using a modified holistically-nested edge detection network.
Medical image analysis
Jun 20, 2019
This paper presents a method for automatic breast pectoral muscle segmentation in mediolateral oblique mammograms using a Convolutional Neural Network (CNN) inspired by the Holistically-nested Edge Detection (HED) network. Most of the existing method...
Improving human cortical sulcal curve labeling in large scale cross-sectional MRI using deep neural networks.
Journal of neuroscience methods
Jun 12, 2019
BACKGROUND: Human cortical primary sulci are relatively stable landmarks and commonly observed across the population. Despite their stability, the primary sulci exhibit phenotypic variability.
Task-Oriented Feature-Fused Network With Multivariate Dataset for Joint Face Analysis.
IEEE transactions on cybernetics
Jun 5, 2019
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...
Unsupervised tumor detection in Dynamic PET/CT imaging of the prostate.
Medical image analysis
Apr 6, 2019
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...
Integrating spatial configuration into heatmap regression based CNNs for landmark localization.
Medical image analysis
Mar 25, 2019
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...
Fully automated radiological analysis of spinal disorders and deformities: a deep learning approach.
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 ...
Automatic 3D cephalometric annotation system using shadowed 2D image-based machine learning.
Physics in medicine and biology
Feb 20, 2019
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 ...
Evaluating reinforcement learning agents for anatomical landmark detection.
Medical image analysis
Feb 14, 2019
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...
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