Found: 12
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U‐Net based deep learning bladder segmentation in CT urography.
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- Medical Physics, 2019, v. 46, n. 4, p. 1752, doi. 10.1002/mp.13438
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- Article
Deep‐learning convolutional neural network: Inner and outer bladder wall segmentation in CT urography.
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- Medical Physics, 2019, v. 46, n. 2, p. 634, doi. 10.1002/mp.13326
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- Article
Deep learning in medical imaging and radiation therapy.
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- Medical Physics, 2019, v. 46, n. 1, p. e1, doi. 10.1002/mp.13264
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- Article
Urinary bladder cancer staging in CT urography using machine learning.
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- Medical Physics, 2017, v. 44, n. 11, p. 5814, doi. 10.1002/mp.12510
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- Article
Urinary bladder segmentation in CT urography using deep-learning convolutional neural network and level sets.
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- Medical Physics, 2016, v. 43, n. 4, p. 1882, doi. 10.1118/1.4944498
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- Article
Computerized Decision Support for Bladder Cancer Treatment Response Assessment in CT Urography: Effect on Diagnostic Accuracy in Multi-Institution Multi-Specialty Study.
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- Tomography: A Journal for Imaging Research, 2022, v. 8, n. 2, p. 644, doi. 10.3390/tomography8020054
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- Article
Intraobserver Variability in Bladder Cancer Treatment Response Assessment With and Without Computerized Decision Support.
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- Tomography: A Journal for Imaging Research, 2020, v. 6, n. 2, p. 194, doi. 10.18383/j.tom.2020.00013
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- Article
Methodology for Good Machine Learning with Multi‐Omics Data.
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- Clinical Pharmacology & Therapeutics, 2024, v. 115, n. 4, p. 745, doi. 10.1002/cpt.3105
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- Article
End-to-end deep learning method for predicting hormonal treatment response in women with atypical endometrial hyperplasia or endometrial cancer.
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- Journal of Medical Imaging, 2024, v. 11, n. 1, p. 17502, doi. 10.1117/1.JMI.11.1.017502
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- Article
Decision region analysis for generalizability of artificial intelligence models: estimating model generalizability in the case of cross-reactivity and population shift.
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- Journal of Medical Imaging, 2024, v. 11, n. 1, p. 14501, doi. 10.1117/1.JMI.11.1.014501
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- Article
SPIE-AAPM-NCI BreastPathQ Challenge: an image analysis challenge for quantitative tumor cellularity assessment in breast cancer histology images following neoadjuvant treatment.
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- Journal of Medical Imaging, 2021, v. 8, n. 3, p. 34501, doi. 10.1117/1.JMI.8.3.034501
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- Article
Evaluation of data augmentation via synthetic images for improved breast mass detection on mammograms using deep learning.
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- Journal of Medical Imaging, 2020, v. 7, n. 1, p. 12703, doi. 10.1117/1.JMI.7.1.012703
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- Article