ArticleRadiological physics and technology2019
A complementary scheme for automated detection of high-uptake regions on dedicated breast PET and whole-body PET/CT.
Article in Radiological physics and technology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 12 citations in OpenAlex.
- Improved denoising scheme using three-dimensional multi-zone convolutional neural filters in dedicated breast positron emission tomography images.Radiological physics and technology · 2025Article
- Effect of radioactivity outside the field of view on image quality of dedicated breast positron emission tomography: preliminary phantom and clinical studies.Annals of nuclear medicine · 2022Article
- Photon counting detectors and their applications ranging from particle physics experiments to environmental radiation monitoring and medical imaging.Radiological physics and technology · 2021Review
- Evaluation of image quality at the detector's edge of dedicated breast positron emission tomography.EJNMMI physics · 2021Article
- Whole Cancer Visualization using Gadobutrol-glucose Solution and 7.0 T Magnetic Resonance Imaging.Journal of medical physicsArticle
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
Abstract
In this study, we aimed to develop a hybrid method for automated detection of high-uptake regions in the breast and axilla using dedicated breast positron-emission tomography (db PET) and whole-body PET/computed tomography (CT) images. In our proposed method, high-uptake regions in the breast and axilla were detected using db PET images and whole-body PET/CT images. In db PET images, high-uptake regions in the breast were detected using adaptive thresholding technique based on the noise characteristics. In whole-body PET/CT images, the region of the breast that includes the axilla was first extracted using CT images. Next, high-uptake regions in the extracted breast region were detected on the PET images. By integration of the results of the two types of PET images, a final candidate region was obtained. In the experiments, the accuracy of extracting the region of the breast and detection ability was evaluated using clinical data. As a result, all breast regions were extracted correctly. The sensitivity of detection was 0.765, and the number of false positive cases were 1.8, which was 30% better than those on whole-body PET/CT alone. These results suggested that the proposed method, combining the two types of PET images is effective for improving detection performance.
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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.