ArticleCancer informatics2014
Medical Image Retrieval: A Multimodal Approach.
Article in Cancer informatics, 2014. 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.
- Mind the gap: challenges and future directions for content-based image retrieval in clinical radiology.Frontiers in radiology · 2026Article
- On image search in histopathology.Journal of pathology informatics · 2024Review
- A Data Ingestion Procedure towards a Medical Images Repository.Sensors (Basel, Switzerland) · 2024Article
- Impact of an online reference system on the diagnosis of rare or atypical abdominal tumors and lesions.Scientific reports · 2024Article
- Deep Attention Fusion Hashing (DAFH) Model for Medical Image Retrieval.Bioengineering (Basel, Switzerland) · 2024Article
- Medical Image Retrieval via Nearest Neighbor Search on Pre-trained Image Features.Knowledge-based systems · 2023Article
- Impact of a content-based image retrieval system on the interpretation of chest CTs of patients with diffuse parenchymal lung disease.European radiology · 2023Article
- Enhancing the Tracking of Seedling Growth Using RGB-Depth Fusion and Deep Learning.Sensors (Basel, Switzerland) · 2021Article
- Deep Bayesian Hashing With Center Prior for Multi-Modal Neuroimage Retrieval.IEEE transactions on medical imaging · 2021Article
- A multi-level similarity measure for the retrieval of the common CT imaging signs of lung diseases.Medical & biological engineering & computing · 2020Article
- Deep Learning Intervention for Health Care Challenges: Some Biomedical Domain Considerations.JMIR mHealth and uHealth · 2019Article
- Radiological images and machine learning: Trends, perspectives, and prospects.Computers in biology and medicine · 2019Review
- Classification of contrast-enhanced spectral mammography (CESM) images.International journal of computer assisted radiology and surgery · 2019Article
- Image Retrieval Based on Local Mesh Vector Co-occurrence Pattern for Medical Diagnosis from MRI Brain Images.Journal of medical systems · 2017Article
- A Multimodal Search Engine for Medical Imaging Studies.Journal of digital imaging · 2017Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Medical imaging is becoming a vital component of war on cancer. Tremendous amounts of medical image data are captured and recorded in a digital format during cancer care and cancer research. Facing such an unprecedented volume of image data with heterogeneous image modalities, it is necessary to develop effective and efficient content-based medical image retrieval systems for cancer clinical practice and research. While substantial progress has been made in different areas of content-based image retrieval (CBIR) research, direct applications of existing CBIR techniques to the medical images produced unsatisfactory results, because of the unique characteristics of medical images. In this paper, we develop a new multimodal medical image retrieval approach based on the recent advances in the statistical graphic model and deep learning. Specifically, we first investigate a new extended probabilistic Latent Semantic Analysis model to integrate the visual and textual information from medical images to bridge the semantic gap. We then develop a new deep Boltzmann machine-based multimodal learning model to learn the joint density model from multimodal information in order to derive the missing modality. Experimental results with large volume of real-world medical images have shown that our new approach is a promising solution for the next-generation medical imaging indexing and retrieval system.
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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.