AIMC Topic: Imaging, Three-Dimensional

Clear Filters Showing 1421 to 1430 of 1894 articles

Concatenated and Connected Random Forests With Multiscale Patch Driven Active Contour Model for Automated Brain Tumor Segmentation of MR Images.

IEEE transactions on medical imaging
Segmentation of brain tumors from magnetic resonance imaging (MRI) data sets is of great importance for improved diagnosis, growth rate prediction, and treatment planning. However, automating this process is challenging due to the presence of severe ...

3-D Fully Convolutional Networks for Multimodal Isointense Infant Brain Image Segmentation.

IEEE transactions on cybernetics
Accurate segmentation of infant brain images into different regions of interest is one of the most important fundamental steps in studying early brain development. In the isointense phase (approximately 6-8 months of age), white matter and gray matte...

Spatial aggregation of holistically-nested convolutional neural networks for automated pancreas localization and segmentation.

Medical image analysis
Accurate and automatic organ segmentation from 3D radiological scans is an important yet challenging problem for medical image analysis. Specifically, as a small, soft, and flexible abdominal organ, the pancreas demonstrates very high inter-patient a...

Respiratory motion correction for free-breathing 3D abdominal MRI using CNN-based image registration: a feasibility study.

The British journal of radiology
OBJECTIVE: Free-breathing abdomen imaging requires non-rigid motion registration of unavoidable respiratory motion in three-dimensional undersampled data sets. In this work, we introduce an image registration method based on the convolutional neural ...

Sliding to predict: vision-based beating heart motion estimation by modeling temporal interactions.

International journal of computer assisted radiology and surgery
PURPOSE: Technical advancements have been part of modern medical solutions as they promote better surgical alternatives that serve to the benefit of patients. Particularly with cardiovascular surgeries, robotic surgical systems enable surgeons to per...

Left Atrial Appendage Segmentation Using Fully Convolutional Neural Networks and Modified Three-Dimensional Conditional Random Fields.

IEEE journal of biomedical and health informatics
Thrombosis has become a global disease threatening human health. The left atrial appendage (LAA) is a major source of thrombosis in patients with atrial fibrillation (AF). Positive correlation exists between LAA volume and AF risk. LAA morphology has...

Alzheimer's disease diagnostics by a 3D deeply supervised adaptable convolutional network.

Frontiers in bioscience (Landmark edition)
Early diagnosis is playing an important role in preventing progress of the Alzheimer's disease (AD). This paper proposes to improve the prediction of AD with a deep 3D Convolutional Neural Network (3D-CNN), which can show generic features capturing A...

Computer Simulation and Optimization of Cranial Vault Distraction.

The Cleft palate-craniofacial journal : official publication of the American Cleft Palate-Craniofacial Association
OBJECTIVE: The objective of this study was to validate the proof of concept of a computer-simulated cranial distraction, demonstrating accurate shape and end volume.

Cleft Skeletal Asymmetry: Asymmetry Index, Classification and Application.

The Cleft palate-craniofacial journal : official publication of the American Cleft Palate-Craniofacial Association
OBJECTIVE: To quantitatively measure the extent of 3D asymmetry of the facial skeleton in patients with unilateral cleft lip and palate (UCLP) using an asymmetry index (AI) approach, and to illustrate the applicability of the index in guiding and mea...

Learning normalized inputs for iterative estimation in medical image segmentation.

Medical image analysis
In this paper, we introduce a simple, yet powerful pipeline for medical image segmentation that combines Fully Convolutional Networks (FCNs) with Fully Convolutional Residual Networks (FC-ResNets). We propose and examine a design that takes particula...