Výsledky vyhledávání - "Sueharu Miyahara"

Akademický článek

The acoustic characteristics of fine crackles predict honeycombing on high-resolution computed tomography

Autor: Toshikazu Fukumitsu, Yasushi Obase, Yuji Ishimatsu, Shota Nakashima, Hiroshi Ishimoto, Noriho Sakamoto, Kosei Nishitsuji, Shunpei Shiwa, Tomoya Sakai, Sueharu Miyahara, Kazuto Ashizawa, Hiroshi Mukae, Ryo Kozu

Publikováno v: BMC Pulmonary Medicine, Vol 19, Iss 1, Pp 1-8 (2019)

Abstract Background Honeycombing on high-resolution computed tomography (HRCT) is a distinguishing feature of usual interstitial pneumonia and predictive of poor outcome in interstitial lung diseases (ILDs). Although fine crackles are common in ILD p

Externí odkaz: https://doaj.org/article/78d38b15cf594c8cb6d81ffb2db7ec58

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Unmixing three types of lung sounds by convex optimization

Autor: Sueharu Miyahara, Tomoya Sakai, Senya Kiyasu

Publikováno v: ICPR

We present a convex optimization technique for unmixing lung sounds to improve computer-aided pulmonary auscultation. An auscultatory sound of a patient with pulmonary disorder may be composed of continuous and discontinuous adventitious sounds as we

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e87429b1dca9e89cfacb50b86c9636b5
https://doi.org/10.1109/icpr.2016.7900074

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The acoustic characteristics of fine crackles predict honeycombing on high-resolution computed tomography

Autor: Kosei Nishitsuji, Yasushi Obase, Yuji Ishimatsu, Ryo Kozu, Hiroshi Mukae, Sueharu Miyahara, Shunpei Shiwa, Tomoya Sakai, Shota Nakashima, Hiroshi Ishimoto, Noriho Sakamoto, Kazuto Ashizawa, Toshikazu Fukumitsu

Publikováno v: BMC Pulmonary Medicine, Vol 19, Iss 1, Pp 1-8 (2019)
BMC Pulmonary Medicine

Background: Honeycombing on high-resolution computed tomography (HRCT) is a distinguishing feature of usual interstitial pneumonia and predictive of poor outcome in interstitial lung diseases (ILDs). Although fine crackles are common in ILD patients,

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::27cba1cf7076e78916d3873defab2f62
https://nagasaki-u.repo.nii.ac.jp/records/267

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Discrimination between healthy subjects and patients with pulmonary emphysema by detection of abnormal respiration

Autor: Masaru Yamashita, Sueharu Miyahara, Shoichi Matsunaga

Publikováno v: ICASSP

In this paper, we propose a robust classification strategy for distinguishing between a healthy subject and a patient with pulmonary emphysema on the basis of lung sounds. A symptom of pulmonary emphysema is that almost all lung sounds include some a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::40a043d0c6277e59c22d930c1f9e16ef
https://nagasaki-u.repo.nii.ac.jp/records/12116

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Classification between normal and abnormal respiratory sounds based on maximum likelihood approach

Autor: Katsuya Yamauchi, Masaru Yamashita, Sueharu Miyahara, Shoichi Matsunaga

Publikováno v: ICASSP

In this paper, we have proposed a novel classification procedure for distinguishing between normal respiratory and abnormal respiratory sounds based on a maximum likelihood approach using hidden Markov models. We have assumed that each inspiratory/ex

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::015d5b4354c7e2f3346454d5e8999be7
https://nagasaki-u.repo.nii.ac.jp/records/16442

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Arbitrary-Shaped Cluster Separation Using One-Dimensional Data Mapping and Histogram Segmentation

Autor: Seiji Hotta, Senya Kiyasu, Sueharu Miyahara

Publikováno v: Journal of Advanced Computational Intelligence and Intelligent Informatics. 11:1136-1143

Of the many clustering methods proposed for separating arbitrarily shaped clusters, most had drawbacks in parameter sensitivity and high-computational cost requiring large amounts of memory. We propose one-dimensional (1D) mapping for separating arbi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::42a5799ffdea284a00968f0b89cec98e
https://doi.org/10.20965/jaciii.2007.p1136

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Detection of Abnormal Lung Sounds Through Investigation of Breathing Cycle

Autor: Sueharu Miyahara, Senya Kiyasu, Mikio Oka, Kohsuke Yanagihara, Tomonari Masada

Publikováno v: The Journal of The Institute of Image Information and Television Engineers. 61:1769-1773

The purpose of our research is to develop a method for recognizing abnormal lung sounds without the need of a medical specialist.Listening to the sounds of the human body is one of the most important methods of checking someone's health. However,iden

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::674381348dbf90215df27778084275d6
https://doi.org/10.3169/itej.61.1769

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Adaptive Subpixel Estimation of Land Cover in a Remotely Sensed Multispectral Image

Autor: Seiji Hotta, Sueharu Miyahara, Kazunori Terashima, Senya Kiyasu

Publikováno v: SICE-ICASE International Joint Conference. 2006:1943-1946

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Land surface corresponding to a pixel of remotely sensed image does not necessarily consist of only one category of objects. Several techniques of subpixel analysis have been developed which estimate the proportion of components

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8fdf8f8628f67d325132e4308bf2a427
http://hdl.handle.net/10069/16324

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