Výsledky vyhledávání - "Jumpei Kuwazuru"

Computer-assisted delineation of lung tumor regions in treatment planning CT images with PET/CT image sets based on an optimum contour selection method

Autor: Hiroshi Honda, Hidetake Yabuuchi, Ze Jin, Katsumasa Nakamura, Hidetaka Arimura, Jumpei Kuwazuru, Hideki Hirata, Taiki Magome, Yoshiyuki Shioyama, Masayuki Sasaki

Publikováno v: Journal of Radiation Research

To assist radiation oncologists in the delineation of tumor regions during treatment planning for lung cancer, we have proposed an automated contouring algorithm based on an optimum contour selection (OCS) method for treatment planning computed tomog

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3bbabafbf7640c14b0dbd0ab22803c8b
http://europepmc.org/articles/PMC4229921

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Computer-assisted framework for machine-learning-based delineation of GTV regions on datasets of planning CT and PET/CT images

Autor: Ze Jin, Hidetake Yabuuchi, Koujiro Ikushima, Hiroshi Honda, Jumpei Kuwazuru, Tomonari Sasaki, Yoshiyuki Shioyama, Hidetaka Arimura, Masayuki Sasaki

Publikováno v: Journal of Radiation Research

We have proposed a computer-assisted framework for machine-learning–based delineation of gross tumor volumes (GTVs) following an optimum contour selection (OCS) method. The key idea of the proposed framework was to feed image features around GTV co

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cda5151d06ebb4fe8e1e3f81404dead7
https://pubmed.ncbi.nlm.nih.gov/27609193

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Automated detection of multiple sclerosis candidate regions in MR images: false-positive removal with use of an ANN-controlled level-set method

Autor: Hidetaka Arimura, Masafumi Ohki, Yukunori Korogi, Yasuo Yamashita, Fukai Toyofuku, Daisuke Yamamoto, Shingo Kakeda, Jumpei Kuwazuru, Taiki Magome

Publikováno v: Radiological Physics and Technology. 5:105-113

Our purpose in this study was to develop an automated segmentation scheme for multiple sclerosis (MS) lesions in magnetic resonance images using an artificial neural network (ANN)-controlled level-set method. Forty-nine slices with T1-weighted, T2-we

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::439e88708722ff3f2edf8d5d2e72bd09
https://doi.org/10.1007/s12194-011-0141-2

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Computational Intelligent Image Analysis for Assisting Radiation Oncologists’ Decision Making in Radiation Treatment Planning

Autor: A. Mizoguchi, Hidetaka Arimura, Genyu Kakiuchi, Jumpei Kuwazuru, Taiki Magome

Publikováno v: Computational Intelligence in Biomedical Imaging ISBN: 9781461472445

This chapter describes the computational image analysis for assisting radiation oncologists’ decision making in radiation treatment planning for high precision radiation therapy. The radiation therapy consists of five steps, i.e., diagnosis, treatm

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::a44f52d870cd6fec16d2e0fbcde9e961
https://doi.org/10.1007/978-1-4614-7245-2_4

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TU-H-CAMPUS-JeP2-03: Machine-Learning-Based Delineation Framework of GTV Regions of Solid and Ground Glass Opacity Lung Tumors at Datasets of Planning CT and PET/CT Images

Autor: Jumpei Kuwazuru, Ze Jin, H Arimura, Masayuki Sasaki, Hidetake Yabuuchi, Hiroyuki Honda, Koujiro Ikushima, Yoshiyuki Shioyama, Tomonari Sasaki

Publikováno v: Medical Physics. 43:3782-3782

Purpose: In radiation treatment planning, delineation of gross tumor volume (GTV) is very important, because the GTVs affect the accuracies of radiation therapy procedure. To assist radiation oncologists in the delineation of GTV regions while treatm

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::bcebd160525d3ba35803f9bc060f7044
https://doi.org/10.1118/1.4957686

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Magnetic Resonance Image Analysis for Brain CAD Systems with Machine Learning

Autor: Hidetaka Arimura, Jumpei Kuwazuru, Yasuo Yamashita, Chiaki Tokunaga

This chapter describes the image analysis for brain Computer-Aided Diagnosis (CAD) systems with machine learning techniques, which could assist radiologists in the detection of such brain diseases as asymptomatic unruptured aneurysms, Alzheimer’s D

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6d6c5eb2a9040e25afbd8b4c01dc12d7
https://doi.org/10.4018/978-1-4666-0059-1.ch013

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Computerized Estimation of Possible Clinical Target Volume Based on Multimodality Images using a Dual Active Contour Model

Autor: Taiki Magome, Hidetaka Arimura, Hiroyuki Honda, Katsumasa Nakamura, Hideki Hirata, E. Taniyama, Fukai Toyofuku, Jumpei Kuwazuru, Masayuki Sasaki, Yoshiyuki Shioyama

Publikováno v: International Journal of Radiation Oncology*Biology*Physics. 81:S830

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::61e9148a61072a6564ac7ec506d710a8
https://doi.org/10.1016/j.ijrobp.2011.06.1465

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