AI Medical Compendium Topic

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Automatic segmentation in image stacks based on multi-constraint level-set evolution.

Bio-medical materials and engineering
Contour extraction of image stacks is a basic task in medical modeling. The existing level-set methods usually suffer from some problems (e.g. serious errors around sharp features, incorrect split of topology and contour occlusions). This paper propo...

Feature-based fuzzy connectedness segmentation of ultrasound images with an object completion step.

Medical image analysis
Medical ultrasound (US) image segmentation and quantification can be challenging due to signal dropouts, missing boundaries, and presence of speckle, which gives images of similar objects quite different appearance. Typically, purely intensity-based ...

Cramér-Rao lower bound calculations for image registration using simulated phenomenology.

Journal of the Optical Society of America. A, Optics, image science, and vision
The Cramér-Rao lower bound (CRLB) is a valuable tool to quantify fundamental limits to estimation problems associated with imaging systems, and has been used previously to study image registration performance bounds. Most existing work, however, assu...

Fast Multiclass Dictionaries Learning With Geometrical Directions in MRI Reconstruction.

IEEE transactions on bio-medical engineering
OBJECTIVE: Improve the reconstructed image with fast and multiclass dictionaries learning when magnetic resonance imaging is accelerated by undersampling the k-space data.

Adaptive Shape Kernel-Based Mean Shift Tracker in Robot Vision System.

Computational intelligence and neuroscience
This paper proposes an adaptive shape kernel-based mean shift tracker using a single static camera for the robot vision system. The question that we address in this paper is how to construct such a kernel shape that is adaptive to the object shape. W...

Temporally Constrained Group Sparse Learning for Longitudinal Data Analysis in Alzheimer's Disease.

IEEE transactions on bio-medical engineering
Sparse learning has been widely investigated for analysis of brain images to assist the diagnosis of Alzheimer's disease and its prodromal stage, i.e., mild cognitive impairment. However, most existing sparse learning-based studies only adopt cross-s...

Semisupervised Tripled Dictionary Learning for Standard-Dose PET Image Prediction Using Low-Dose PET and Multimodal MRI.

IEEE transactions on bio-medical engineering
OBJECTIVE: To obtain high-quality positron emission tomography (PET) image with low-dose tracer injection, this study attempts to predict the standard-dose PET (S-PET) image from both its low-dose PET (L-PET) counterpart and corresponding magnetic re...