Texture based feature extraction methods for content based medical image retrieval systems.

Biomed Mater Eng

Department of Software Engineering, Faculty of Technology, Fırat University, 23119, Elazig, Turkey.

Published: June 2015

The developments of content based image retrieval (CBIR) systems used for image archiving are continued and one of the important research topics. Although some studies have been presented general image achieving, proposed CBIR systems for archiving of medical images are not very efficient. In presented study, it is examined the retrieval efficiency rate of spatial methods used for feature extraction for medical image retrieval systems. The investigated algorithms in this study depend on gray level co-occurrence matrix (GLCM), gray level run length matrix (GLRLM), and Gabor wavelet accepted as spatial methods. In the experiments, the database is built including hundreds of medical images such as brain, lung, sinus, and bone. The results obtained in this study shows that queries based on statistics obtained from GLCM are satisfied. However, it is observed that Gabor Wavelet has been the most effective and accurate method.

Download full-text PDF

Source
http://dx.doi.org/10.3233/BME-141127DOI Listing

Publication Analysis

Top Keywords

image retrieval
12
feature extraction
8
content based
8
medical image
8
retrieval systems
8
cbir systems
8
medical images
8
spatial methods
8
gray level
8
gabor wavelet
8

Similar Publications

Open-Source Large Language Models in Radiology: A Review and Tutorial for Practical Research and Clinical Deployment.

Radiology

January 2025

From the University of Maryland Medical Intelligent Imaging (UM2ii) Center, Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, 22 S Greene St, Baltimore, MD 21201 (C.H.S., A.K., V.P., F.X.D.); Departments of Radiology, Medicine, and Biomedical Data Science, Stanford University, Palo Alto, Calif (C.P.L.); Department of Computer Science and Electrical Engineering, College of Engineering and Information Technology, University of Maryland, Baltimore County, Baltimore, Md (A.J.); Department of Computer Science, University of Maryland, College Park, College Park, Md (H.H.); and University of Maryland Institute for Health Computing, University of Maryland, North Bethesda, Md (H.H., F.X.D.).

Integrating large language models (LLMs) into health care holds substantial potential to enhance clinical workflows and care delivery. However, LLMs also pose serious risks if integration is not thoughtfully executed, with complex challenges spanning accuracy, accessibility, privacy, and regulation. Proprietary commercial LLMs (eg, GPT-4 [OpenAI], Claude 3 Sonnet and Claude 3 Opus [Anthropic], Gemini [Google]) have received much attention from researchers in the medical domain, including radiology.

View Article and Find Full Text PDF

Natural language processing-based classification of early Alzheimer's disease from connected speech.

Alzheimers Dement

January 2025

Laboratory for Cognitive Neurology, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven, Belgium.

Introduction: The automated analysis of connected speech using natural language processing (NLP) emerges as a possible biomarker for Alzheimer's disease (AD). However, it remains unclear which types of connected speech are most sensitive and specific for the detection of AD.

Methods: We applied a language model to automatically transcribed connected speech from 114 Flemish-speaking individuals to first distinguish early AD patients from amyloid negative cognitively unimpaired (CU) and then amyloid negative from amyloid positive CU individuals using five different types of connected speech.

View Article and Find Full Text PDF

A previous study employing fMRI measures of retrieval-related cortical reinstatement reported that young, but not older, adults employ 'retrieval gating' to attenuate aspects of an episodic memory that are irrelevant to the retrieval goal. We examined whether the weak memories of the older adults in that study rendered goal-irrelevant memories insufficiently intrusive to motivate retrieval gating. Young and older participants studied words superimposed on rural or urban scenes, or on pixelated backgrounds.

View Article and Find Full Text PDF

Background The incidence of margin re-excision following breast conserving surgery (BCS) is a quality measure in the National Health Service. The threshold is less than 20% of all BCS procedures. Despite three decades of studies and a wealth of literature identifying multiple factors associated with increased risk for margin involvement, an accepted threshold rate affecting one in five procedures remains high.

View Article and Find Full Text PDF

Islet transplantation and more recently stem cell-derived islets were shown to successfully re-establish glycemic control in people with type 1 diabetes under immunosuppression. These results were achieved through intraportal infusion which leads to early graft losses and limits the capacity to contain and retrieve implanted cells in case of adverse events. Extra-hepatic sites and encapsulation devices have been developed to address these challenges and potentially create an immunoprotective or immune-privileged environment.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!