ReviewJournal of digital imaging2013
Content-based medical image retrieval: a survey of applications to multidimensional and multimodality data.
Review in Journal of digital imaging, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed.
- A 3-D Cross-Modal Keypoint Descriptor for MR-US Matching and Registration.IEEE transactions on medical imaging · 2026Article
- Content-Based Histopathological Image Retrieval.Sensors (Basel, Switzerland) · 2025Article
- On image search in histopathology.Journal of pathology informatics · 2024Review
- Novel in-house knowledge-based automated planning system for lung cancer treated with intensity-modulated radiotherapy.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2024Article
- A New Approach for Effective Retrieval of Medical Images: A Step towards Computer-Assisted Diagnosis.Journal of imaging · 2024Article
- Improving the Automatic Classification of Brain MRI Acquisition Contrast with Machine Learning.Journal of digital imaging · 2023Article
- Using DICOM Metadata for Radiological Image Series Categorization: a Feasibility Study on Large Clinical Brain MRI Datasets.Journal of digital imaging · 2020Article
- Deep learning can be used to train naïve, nonprofessional observers to detect diagnostic visual patterns of certain cancers in mammograms: a proof-of-principle study.Journal of medical imaging (Bellingham, Wash.) · 2020Article
- A spatial neighborhood methodology for computing and analyzing lymph node carcinoma similarity in precision medicine.Journal of biomedical informatics · 2020Article
- Medical Image Retrieval Using Empirical Mode Decomposition with Deep Convolutional Neural Network.BioMed research international · 2020Article
- Cohort-based T-SSIM Visual Computing for Radiation Therapy Prediction and Exploration.IEEE transactions on visualization and computer graphics · 2020Article
- Content based medical image retrieval based on new efficient local neighborhood wavelet feature descriptor.Biomedical engineering letters · 2019Article
- Deep Convolutional Hashing for Low-Dimensional Binary Embedding of Histopathological Images.IEEE journal of biomedical and health informatics · 2019Article
- A rotation and translation invariant method for 3D organ image classification using deep convolutional neural networks.PeerJ. Computer science · 2019Article
- Automated Anatomic Labeling Architecture for Content Discovery in Medical Imaging Repositories.Journal of medical systems · 2018Article
- Overview on subjective similarity of images for content-based medical image retrieval.Radiological physics and technology · 2018Review
- Medical Image Retrieval Using Multi-Texton Assignment.Journal of digital imaging · 2018Article
- Content-based image retrieval for Lung Nodule Classification Using Texture Features and Learned Distance Metric.Journal of medical systems · 2017Article
- SiNC: Saliency-injected neural codes for representation and efficient retrieval of medical radiographs.PloS one · 2017Article
- Cloud-Based NoSQL Open Database of Pulmonary Nodules for Computer-Aided Lung Cancer Diagnosis and Reproducible Research.Journal of digital imaging · 2016Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Medical imaging is fundamental to modern healthcare, and its widespread use has resulted in the creation of image databases, as well as picture archiving and communication systems. These repositories now contain images from a diverse range of modalities, multidimensional (three-dimensional or time-varying) images, as well as co-aligned multimodality images. These image collections offer the opportunity for evidence-based diagnosis, teaching, and research; for these applications, there is a requirement for appropriate methods to search the collections for images that have characteristics similar to the case(s) of interest. Content-based image retrieval (CBIR) is an image search technique that complements the conventional text-based retrieval of images by using visual features, such as color, texture, and shape, as search criteria. Medical CBIR is an established field of study that is beginning to realize promise when applied to multidimensional and multimodality medical data. In this paper, we present a review of state-of-the-art medical CBIR approaches in five main categories: two-dimensional image retrieval, retrieval of images with three or more dimensions, the use of nonimage data to enhance the retrieval, multimodality image retrieval, and retrieval from diverse datasets. We use these categories as a framework for discussing the state of the art, focusing on the characteristics and modalities of the information used during medical image retrieval.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.