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Chisako Muramatsu, Ph.D.

Affiliations: 
2008 University of Chicago, Chicago, IL 
Area:
Radiology
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Kunio Doi grad student 2008 Chicago
 (Investigation of similarity measures for selection of similar images in computer -aided diagnosis of breast lesions on mammograms.)

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Muramatsu C, Nishio M, Goto T, et al. (2020) Improving breast mass classification by shared data with domain transformation using a generative adversarial network. Computers in Biology and Medicine. 119: 103698
Muramatsu C. (2018) Overview on subjective similarity of images for content-based medical image retrieval. Radiological Physics and Technology
Hatanaka Y, Tajima M, Kawasaki R, et al. (2017) Retinal biometrics based on Iterative Closest Point algorithm. Conference Proceedings : ... Annual International Conference of the Ieee Engineering in Medicine and Biology Society. Ieee Engineering in Medicine and Biology Society. Annual Conference. 2017: 373-376
Sayed Aluwee SA, Zhou X, Kato H, et al. (2017) Evaluation of pre-surgical models for uterine surgery by use of three-dimensional printing and mold casting. Radiological Physics and Technology
Hiramatsu Y, Muramatsu C, Kobayashi H, et al. (2017) Automated detection of masses on whole breast volume ultrasound scanner: false positive reduction using deep convolutional neural network Proceedings of Spie. 10134
Miki Y, Muramatsu C, Hayashi T, et al. (2017) Tooth labeling in cone-beam CT using deep convolutional neural network for forensic identification Proceedings of Spie. 10134
Fukui T, Kita K, Kamemoto H, et al. (2017) Evaluation of age-related changes with cross-sectional CT imaging of teeth Proceedings of Spie. 10134
Kamiya N, Ieda K, Zhou X, et al. (2017) Automated analysis of whole skeletal muscle for muscular atrophy detection of ALS in whole-body CT images: preliminary study Proceedings of Spie. 10134: 1013442
Miki Y, Muramatsu C, Hayashi T, et al. (2016) Classification of teeth in cone-beam CT using deep convolutional neural network. Computers in Biology and Medicine. 80: 24-29
Muramatsu C, Hara T, Endo T, et al. (2016) Breast mass classification on mammograms using radial local ternary patterns. Computers in Biology and Medicine. 72: 43-53
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