ArticleMedical physics2022
Quantification of uptake in pelvis F-18 FLT PET-CT images using a 3D localization and segmentation CNN.
Article in Medical physics, 2022. 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, 13 citations in OpenAlex.
- Hybrid deep learning enables multi-institutional delineation of active bone marrow for gynecologic radiotherapy.Physics and imaging in radiation oncology · 2025Article
- Lumbar and Thoracic Vertebrae Segmentation in CT Scans Using a 3D Multi-Object Localization and Segmentation CNN.Tomography (Ann Arbor, Mich.) · 2024Article
- Head and Neck Cancer Segmentation in FDG PET Images: Performance Comparison of Convolutional Neural Networks and Vision Transformers.Tomography (Ann Arbor, Mich.) · 2023Article
- Review
- Estimating normal metabolic activity for disease quantification via PET/CT images.Proceedings of SPIE--the International Society for Optical Engineering · 2023Article
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
purposeThe purpose of this work was to develop and validate a deep convolutional neural network (CNN) approach for the automated pelvis segmentation in computed tomography (CT) scans to enable the quantification of active pelvic bone marrow by means of Fluorothymidine F-18 (FLT) tracer uptake measurement in positron emission tomography (PET) scans. This quantification is a critical step in calculating bone marrow dose for radiopharmaceutical therapy clinical applications as well as external beam radiation doses.
methodsAn approach for the combined localization and segmentation of the pelvis in CT volumes of varying sizes, ranging from full-body to pelvis CT scans, was developed that utilizes a novel CNN architecture in combination with a random sampling strategy. The method was validated on 34 planning CT scans and 106 full-body FLT PET-CT scans using a cross-validation strategy. Specifically, two different training and CNN application options were studied, quantitatively assessed, and statistically compared.
resultsThe proposed method was able to successfully locate and segment the pelvis in all test cases. On all data sets, an average Dice coefficient of 0.9396
conclusionsThe proposed method enables the efficient calculation of FLT uptake in the pelvis. Thus, it represents a valuable tool to facilitate bone marrow preserving adaptive radiation therapy and radiopharmaceutical dose calculation. Furthermore, the method can be adapted to process other bone structures as well as organs.
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