Fully automated prostate whole gland and central gland segmentation on MRI using holistically nested networks with short connections

Accurate and automated prostate whole gland and central gland segmentations on MR images are essential for aiding any prostate cancer diagnosis system. Our work presents a 2-D orthogonal deep learning method to automatically segment the whole prostate and central gland from T2-weighted axial-only MR...

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Tallennettuna:
Bibliografiset tiedot
Julkaisussa:J Med Imaging (Bellingham)
Päätekijät: Cheng, Ruida, Lay, Nathan, Roth, Holger R., Turkbey, Baris, Jin, Dakai, Gandler, William, McCreedy, Evan S., Pohida, Tom, Pinto, Peter, Choyke, Peter, McAuliffe, Matthew J., Summers, Ronald M.
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: Society of Photo-Optical Instrumentation Engineers 2019
Aiheet:
Image Processing
Linkit:https://ncbi.nlm.nih.gov/pmc/articles/PMC6551111/
https://ncbi.nlm.nih.gov/pubmed/31205977
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1117/1.JMI.6.2.024007
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