AIMC Topic: Image Processing, Computer-Assisted

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Combined fuzzy logic and random walker algorithm for PET image tumor delineation.

Nuclear medicine communications
PURPOSE: The random walk (RW) technique serves as a powerful tool for PET tumor delineation, which typically involves significant noise and/or blurring. One challenging step is hard decision-making in pixel labeling. Fuzzy logic techniques have achie...

Feature-Motivated Simplified Adaptive PCNN-Based Medical Image Fusion Algorithm in NSST Domain.

Journal of digital imaging
Multimodality medical image fusion plays a vital role in diagnosis, treatment planning, and follow-up studies of various diseases. It provides a composite image containing critical information of source images required for better localization and def...

[Machine Learning for Computer-aided Diagnosis].

Igaku butsuri : Nihon Igaku Butsuri Gakkai kikanshi = Japanese journal of medical physics : an official journal of Japan Society of Medical Physics
Machine learning algorithms are to analyze any dataset to extract data-driven model, prediction rule, or decision rule from the dataset. Various machine learning algorithms are now used to develop high-performance medical image processing systems suc...

Bioimage Informatics for Big Data.

Advances in anatomy, embryology, and cell biology
Bioimage informatics is a field wherein high-throughput image informatics methods are used to solve challenging scientific problems related to biology and medicine. When the image datasets become larger and more complicated, many conventional image a...

Automatic anatomy recognition in whole-body PET/CT images.

Medical physics
PURPOSE: Whole-body positron emission tomography/computed tomography (PET/CT) has become a standard method of imaging patients with various disease conditions, especially cancer. Body-wide accurate quantification of disease burden in PET/CT images is...

Medical image segmentation via atlases and fuzzy object models: Improving efficacy through optimum object search and fewer models.

Medical physics
PURPOSE: Statistical object shape models (SOSMs), known as probabilistic atlases, are popular in medical image segmentation. They register an image into the atlas coordinate system, such that a desired object can be delineated from the constraints of...

Enhancing atlas based segmentation with multiclass linear classifiers.

Medical physics
PURPOSE: To present a method to enrich atlases for atlas based segmentation. Such enriched atlases can then be used as a single atlas or within a multiatlas framework.

The model for Fundamentals of Endovascular Surgery (FEVS) successfully defines the competent endovascular surgeon.

Journal of vascular surgery
OBJECTIVE: Fundamental skills testing is now required for certification in general surgery. No model for assessing fundamental endovascular skills exists. Our objective was to develop a model that tests the fundamental endovascular skills and differe...

Deploying swarm intelligence in medical imaging identifying metastasis, micro-calcifications and brain image segmentation.

IET systems biology
This study proposes an umbrella deployment of swarm intelligence algorithm, such as stochastic diffusion search for medical imaging applications. After summarising the results of some previous works which shows how the algorithm assists in the identi...

Classification of Parkinson's Disease Gait Using Spatial-Temporal Gait Features.

IEEE journal of biomedical and health informatics
Quantitative gait assessment is important in diagnosis and management of Parkinson's disease (PD); however, gait characteristics of a cohort are dispersed by patient physical properties including age, height, body mass, and gender, as well as walking...