Mikinao Oiwa - researchr alias

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Viewing Publication 1 - 8 from 8

2022

Intrinsic subtype classification of breast lesions on mammograms by contrastive learningChisako Muramatsu, Mikinao Oiwa, Tomonori Kawasaki, Hiroshi Fujita 0001. micad 2022: [doi]

2020

Improving breast mass classification by shared data with domain transformation using a generative adversarial networkChisako Muramatsu, Mizuho Nishio, Takuma Goto, Mikinao Oiwa, Takako Morita, Masahiro Yakami, Takeshi Kubo, Kaori Togashi, Hiroshi Fujita 0001. cbm, 119:103698, 2020. [doi]

2018

Similarity estimation for reference image retrieval in mammograms using convolutional neural networkChisako Muramatsu, Shunichi Higuchi, Takako Morita, Mikinao Oiwa, Hiroshi Fujita 0001. micad 2018: [doi]

Retrieval of reference images of breast masses on mammograms by similarity space modelingChisako Muramatsu, Shunichi Higuchi, Takako Morita, Mikinao Oiwa, Tomonori Kawasaki, Hiroshi Fujita 0001. iwbi 2018: 1071809 [doi]

2014

Development of New Imaging System Based on Grating Interferometry : Preclinical Study in Breast ImagingTokiko Endo, Shu Ichihara, Suzuko Moritani, Mikinao Oiwa, Misaki Shiraiwa, Takako Morita, Yasuyuki Sato, Junko Kiyohara, Sumiya Nagatsuka. mammo 2014: 488-493 [doi]

2013

2012

Correspondence among Subjective and Objective Similarities and Pathologic Types of Breast Masses on Digital MammographyChisako Muramatsu, Kohei Nishimura, Mikinao Oiwa, Misaki Shiraiwa, Tokiko Endo, Kunio Doi, Hiroshi Fujita. mammo 2012: 450-457 [doi]

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