Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/2832
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Tsapatsoulis, Nicolas | - |
dc.contributor.author | Schnorrenberg, Frank | - |
dc.contributor.author | Pattichis, Constantinos S. | - |
dc.contributor.author | Kollias, Stefanos D. | - |
dc.date.accessioned | 2015-05-27T12:30:52Z | - |
dc.date.accessioned | 2015-12-02T12:06:18Z | - |
dc.date.available | 2015-05-27T12:30:52Z | - |
dc.date.available | 2015-12-02T12:06:18Z | - |
dc.date.issued | 1997 | - |
dc.identifier.citation | IEEE International Conference on Image Processing, 1997, Santa Barbara, California, USA, 26-29 October | en_US |
dc.identifier.isbn | 0-8186-8183-7 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.14279/2832 | - |
dc.description.abstract | A study for breast cancer nuclei detection is presented. The proposed algorithm determines the centers of nuclei in biopsy images using block-based processing of the images followed by singular value decomposition of each block. The normalized singular value vector, which consists of the normalized singular values of the block in decreasing order, is fed as the input to an appropriate neural network which classifies the block into nuclei and background ones. Examples are presented which illustrate the ability of the proposed technique to model the knowledge provided by experts in the nuclei detection task | en_US |
dc.format | en_US | |
dc.language.iso | en | en_US |
dc.subject | Biopsy | en_US |
dc.subject | Breast cancer | en_US |
dc.subject | Cancer detection | en_US |
dc.subject | Feature extraction | en_US |
dc.subject | Image analysis | en_US |
dc.subject | Multi-layer neural network | en_US |
dc.subject | Neural networks | en_US |
dc.subject | Singular value decomposition | en_US |
dc.title | An image analysis system for automated detection of breast cancer nuclei | en_US |
dc.type | Conference Papers | en_US |
dc.collaboration | National Technical University Of Athens | en_US |
dc.subject.category | Clinical Medicine | en_US |
dc.review | Peer Reviewed | en |
dc.country | Greece | en_US |
dc.subject.field | Medical and Health Sciences | en_US |
dc.relation.conference | IEEE International Conference on Image Processing | en_US |
dc.identifier.doi | 10.1109/ICIP.1997.632170 | en_US |
dc.dept.handle | 123456789/54 | en |
cut.common.academicyear | 2020-2021 | en_US |
item.openairetype | conferenceObject | - |
item.cerifentitytype | Publications | - |
item.fulltext | No Fulltext | - |
item.grantfulltext | none | - |
item.openairecristype | http://purl.org/coar/resource_type/c_c94f | - |
item.languageiso639-1 | en | - |
crisitem.author.dept | Department of Communication and Marketing | - |
crisitem.author.faculty | Faculty of Communication and Media Studies | - |
crisitem.author.orcid | 0000-0002-6739-8602 | - |
crisitem.author.parentorg | Faculty of Communication and Media Studies | - |
Appears in Collections: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
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