ArticleIEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society2012
Content-based microscopic image retrieval system for multi-image queries.
Article in IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Web engine for tumor pathology image retrievals on massive scales.bioRxiv : the preprint server for biology · 2025Article
- On image search in histopathology.Journal of pathology informatics · 2024Review
- Synergies and Challenges in the Preclinical and Clinical Implementation of Pathology Artificial Intelligence Applications.Mayo Clinic proceedings. Digital health · 2023Review
- Fast and scalable search of whole-slide images via self-supervised deep learning.Nature biomedical engineering · 2022Article
- Role of AI and Histopathological Images in Detecting Prostate Cancer: A Survey.Sensors (Basel, Switzerland) · 2021Review
- An Efficient Content-Based Image Retrieval System for the Diagnosis of Lung Diseases.Journal of digital imaging · 2020Article
- Towards personalized computational oncology: from spatial models of tumour spheroids, to organoids, to tissues.Journal of the Royal Society, Interface · 2018Review
- Informatics Approaches to Address New Challenges in the Classification of Lymphoid Malignancies.JCO clinical cancer informatics · 2018Review
- A Robust Actin Filaments Image Analysis Framework.PLoS computational biology · 2016Article
- Automated prostate tissue referencing for cancer detection and diagnosis.BMC bioinformatics · 2016Article
- Scalable analysis of Big pathology image data cohorts using efficient methods and high-performance computing strategies.BMC bioinformatics · 2015Article
- A multi-resolution textural approach to diagnostic neuropathology reporting.Journal of neuro-oncology · 2015Article
- Content-based histopathology image retrieval using CometCloud.BMC bioinformatics · 2014Article
- Parallel content-based sub-image retrieval using hierarchical searching.Bioinformatics (Oxford, England) · 2014Article
- Content-based medical image retrieval: a survey of applications to multidimensional and multimodality data.Journal of digital imaging · 2013Review
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2 authors.
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Abstract
In this paper, we describe the design and development of a multitiered content-based image retrieval (CBIR) system for microscopic images utilizing a reference database that contains images of more than one disease. The proposed CBIR system uses a multitiered approach to classify and retrieve microscopic images involving their specific subtypes, which are mostly difficult to discriminate and classify. This system enables both multi-image query and slide-level image retrieval in order to protect the semantic consistency among the retrieved images. New weighting terms, inspired from information retrieval theory, are defined for multiple-image query and retrieval. The performance of the system was tested on a dataset including 1666 imaged high power fields extracted from 57 follicular lymphoma (FL) tissue slides with three subtypes and 44 neuroblastoma (NB) tissue slides with four subtypes. Each slide is semantically annotated according to their subtypes by expert pathologists. By using leave-one-slide out testing scheme, the multi-image query algorithm with the proposed weighting strategy achieves about 93% and 86% of average classification accuracy at the first rank retrieval, outperforming the image-level retrieval accuracy by about 38 and 26 percentage points, for FL and NB diseases, respectively.
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