In this paper, we propose a novel scheme for efficient content-based medical image retrieval, formalized according to the PAtterns for Next generation DAtabase systems (PANDA) framework for pattern representation and management. The proposed scheme involves block-based low-level feature extraction from images followed by the clustering of the feature space to form higher-level, semantically meaningful patterns. The clustering of the feature space is realized by an expectation-maximization algorithm that uses an iterative approach to automatically determine the number of clusters. Then, the 2-component property of PANDA is exploited: the similarity between two clusters is estimated as a function of the similarity of both their structures and the measure components. Experiments were performed on a large set of reference radiographic images, using different kinds of features to encode the low-level image content. Through this experimentation, it is shown that the proposed scheme can be efficiently and effectively applied for medical image retrieval from large databases, providing unsupervised semantic interpretation of the results, which can be further extended by knowledge representation methodologies.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1109/TITB.2008.923144 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Technological Adjuncts to Streamline Patient Recruitment, Informed Consent, and Data Management Processes in Clinical Research: Observational Study.
JMIR Form Res
January 2025
Northwestern Medicine, Chicago, IL, United States.
Background: Patient recruitment and data management are laborious, resource-intensive aspects of clinical research that often dictate whether the successful completion of studies is possible. Technological advances present opportunities for streamlining these processes, thus improving completion rates for clinical research studies.
Objective: This paper aims to demonstrate how technological adjuncts can enhance clinical research processes via automation and digital integration.
Design strategies and biomedical applications of organic NIR-IIb fluorophores.
Chem Commun (Camb)
January 2025
Marshall Laboratory of Biomedical Engineering, International Cancer Center, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Laboratory of Evolutionary Theranostics (LET), School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen 518055, China.
The introduction of fluorescence imaging (FLI) in near-infrared II sub-channels (NIR-IIb, 1500-1700 nm) has revolutionized the ability to explore complex patho-physiological settings . Despite the transformative potentials, the development of organic NIR IIb dyes encounters considerable difficulties, and only a limited number of such fluorophores have been developed so far. This review systematically introduces design strategies of organic NIR-IIb fluorophores classified by molecular scaffolds, mainly including cyanine dyes and D-A-D small molecule dyes.
View Article and Find Full Text PDFQuantitative Analysis of Mitochondria-Associated Endoplasmic Reticulum Membrane (MAM) Stabilization in a Neural Model of Alzheimer's Disease (AD).
J Vis Exp
January 2025
Genetics and Aging Research Unit, MassGeneral Institute for Neurodegenerative Disease, Henry and Allison McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Harvard Medical School;
A method to quantitate the stabilization of Mitochondria-Associated endoplasmic reticulum Membranes (MAMs) in a 3-dimensional (3D) neural model of Alzheimer's disease (AD) is presented here. To begin, fresh human neuro progenitor ReN cells expressing β-amyloid precursor protein (APP) containing familial Alzheimer's disease (FAD) or naïve ReN cells are grown in thin (1:100) Matrigel-coated tissue culture plates. After the cells reach confluency, these are electroporated with expression plasmids encoding red fluorescence protein (RFP)-conjugated mitochondria-binding sequence of AKAP1(34-63) (Mito-RFP) that detects mitochondria or constitutive MAM stabilizers MAM 1X or MAM 9X that stabilize tight (6 nm ± 1 nm gap width) or loose (24 nm ± 3 nm gap width) MAMs, respectively.
View Article and Find Full Text PDFDiagnostic accuracy of node-RADS for the detection of lymph node invasion: a systematic review and meta-analysis.
Eur Radiol
January 2025
Department of Urological Surgical, JiangNan University Medical Center, Wuxi, China.
Objective: To conduct a meta-analysis assessing the diagnostic performance of the node reporting and data system (Node-RADS) for detecting lymph node (LN) invasion.
Method: We performed a systematic literature search of online scientific publication databases from inception up to July 31, 2024. We used the quality assessment of diagnostic accuracy studies-2 (QUADAS-2) to assess the study quality, and heterogeneity was determined by the Q-test and measured with I statistics.
Preclinical evaluation of zirconium-89 labeled anti-Trop2 antibody-drug conjugate (Trodelvy) for imaging in gastric cancer and triple-negative breast cancer.
Eur J Nucl Med Mol Imaging
January 2025
Departments of Radiology and Medical Physics, University of Wisconsin - Madison, Madison, WI, 53705, USA.
Purpose: Trophoblast cell-surface antigen 2 (Trop2) is overexpressed in various solid tumors and contributes to tumor progression, while its expression remains low in normal tissues. Trop2-targeting antibody-drug conjugate (ADC), sacituzumab govitecan-hziy (Trodelvy), has shown efficacy in targeting this antigen. Leveraging the enhanced specificity of ADCs, we conducted the first immunoPET imaging study of Trop2 expression in gastric cancer (GC) and triple-negative breast cancer (TNBC) models using Zr-labeled Trodelvy ([Zr]Zr-DFO-Trodelvy).
View Article and Find Full Text PDFWant 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!