Kidney Tumor Segmentation Using Deep Learning
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
www.ijsr.net | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064


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Research Paper | Computers in Biology and Medicine | India | Volume 8 Issue 12, December 2019

Kidney Tumor Segmentation Using Deep Learning

Prashant Jadiya

Proper segmentation of Kidney Tumors can assist doctors to detect and diagnose diseases. When it comes to segmentation, U-Net is arguably the most successful segmentation architecture in the medical domain. In this paper, we address the challenge of simultaneous semantic segmentation of kidney tumor and proposed multidimensional 3D U-Net with an attempt to improve it with V-Net and Auto-Encoder architecture. Due to marginally higher dice scores, it was very difficult to choose architecture that will be accurate for segmentation. We did experiment for training of 190 cases that is provided by Kidney Tumor Segmentation Challenge database.

Keywords: Medical Segmentation, Kidney Tumor Nephrometry Segmentation, Multidimensional images, Neural Network, Auto-Encoder

Edition: Volume 8 Issue 12, December 2019

Pages: 1746 - 1749

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How to Cite this Article?

Prashant Jadiya, "Kidney Tumor Segmentation Using Deep Learning", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=ART20203792, Volume 8 Issue 12, December 2019, 1746 - 1749

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