AIMC Topic: Tomography, X-Ray Computed

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Iterative Low-Dose CT Reconstruction With Priors Trained by Artificial Neural Network.

IEEE transactions on medical imaging
Dose reduction in computed tomography (CT) is essential for decreasing radiation risk in clinical applications. Iterative reconstruction algorithms are one of the most promising way to compensate for the increased noise due to reduction of photon flu...

Urinary bladder cancer staging in CT urography using machine learning.

Medical physics
PURPOSE: To evaluate the feasibility of using an objective computer-aided system to assess bladder cancer stage in CT Urography (CTU).

Automatic Categorization and Scoring of Solid, Part-Solid and Non-Solid Pulmonary Nodules in CT Images with Convolutional Neural Network.

Scientific reports
We present a computer-aided diagnosis system (CADx) for the automatic categorization of solid, part-solid and non-solid nodules in pulmonary computerized tomography images using a Convolutional Neural Network (CNN). Provided with only a two-dimension...

Deep learning of the sectional appearances of 3D CT images for anatomical structure segmentation based on an FCN voting method.

Medical physics
PURPOSE: We propose a single network trained by pixel-to-label deep learning to address the general issue of automatic multiple organ segmentation in three-dimensional (3D) computed tomography (CT) images. Our method can be described as a voxel-wise ...

Automatic detection of hemorrhagic pericardial effusion on PMCT using deep learning - a feasibility study.

Forensic science, medicine, and pathology
Post mortem computed tomography (PMCT) can be used as a triage tool to better identify cases with a possibly non-natural cause of death, especially when high caseloads make it impossible to perform autopsies on all cases. Substantial data can be gene...

3D Reconstruction of human bones based on dictionary learning.

Medical engineering & physics
An effective method for reconstructing a 3D model of human bones from computed tomography (CT) image data based on dictionary learning is proposed. In this study, the dictionary comprises the vertices of triangular meshes, and the sparse coefficient ...

Bladder Cancer Treatment Response Assessment in CT using Radiomics with Deep-Learning.

Scientific reports
Cross-sectional X-ray imaging has become the standard for staging most solid organ malignancies. However, for some malignancies such as urinary bladder cancer, the ability to accurately assess local extent of the disease and understand response to sy...

Lung disease stratification using amalgamation of Riesz and Gabor transforms in machine learning framework.

Computers in biology and medicine
Lung disease risk stratification is important for both diagnosis and treatment planning, particularly in biopsies and radiation therapy. Manual lung disease risk stratification is challenging because of: (a) large lung data sizes, (b) inter- and intr...

Fuzzy Object Skeletonization: Theory, Algorithms, and Applications.

IEEE transactions on visualization and computer graphics
Skeletonization offers a compact representation of an object while preserving important topological and geometrical features. Literature on skeletonization of binary objects is quite mature. However, challenges involved with skeletonization of fuzzy ...