Medical Image Retrieval
11 papers with code • 1 benchmarks • 3 datasets
Benchmarks
These leaderboards are used to track progress in Medical Image Retrieval
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
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BreakHis
BreastDICOM4
BreastRates4
Most implemented papers
BreastScreening: On the Use of Multi-Modality in Medical Imaging Diagnosis
This paper describes the field research, design and comparative deployment of a multimodal medical imaging user interface for breast screening.
EndoMapper dataset of complete calibrated endoscopy procedures
Computer-assisted systems are becoming broadly used in medicine.
Barcode Annotations for Medical Image Retrieval: A Preliminary Investigation
This paper proposes to generate and to use barcodes to annotate medical images and/or their regions of interest such as organs, tumors and tissue types.
Medical Image Retrieval using Deep Convolutional Neural Network
himanshunaidu/cnn_adnan_fruit
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The learned features and the classification results are used to retrieve medical images.
Deep Triplet Hashing Network for Case-based Medical Image Retrieval
The triplet cross-entropy loss can help to map the classification information of images and similarity between images into the hash codes.
CNN Based Autoencoder Application in Breast Cancer Image Retrieval
forderation/breast-cancer-retrieval
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International Seminar on Intelligent Technology and Its Applications (ISITIA) 2021
Overall, the results of image retrieval in breast cancer applying the CNN based Autoencoder method achieved higher performance compared to the method used in the previous study with an average precision of 0. 9237 in the mainclass dataset category and 0. 6825 in the subclass dataset category.
TorchXRayVision: A library of chest X-ray datasets and models
TorchXRayVision is an open source software library for working with chest X-ray datasets and deep learning models.
Medical Image Retrieval via Nearest Neighbor Search on Pre-trained Image Features
deepaknlp/dls
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We extensively tested the proposed NNS approach and compared the performance with state-of-the-art NNS approaches on benchmark datasets and our created medical image datasets.
Sketch-based Medical Image Retrieval
kaz-k/sketch-based-medical-image-retrieval
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As a result, our SBMIR system enabled users to overcome previous challenges, including image retrieval based on fine-grained image characteristics, image retrieval without example images, and image retrieval for isolated samples.
3D-MIR: A Benchmark and Empirical Study on 3D Medical Image Retrieval in Radiology
The increasing use of medical imaging in healthcare settings presents a significant challenge due to the increasing workload for radiologists, yet it also offers opportunity for enhancing healthcare outcomes if effectively leveraged.
