whisper
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Chao-Hui Huang, Antoine Veillard, Nicolas Lom´eniea, Daniel Racoceanu, Ludovic Roux
Time-efficient sparse analysis of histopathological Whole Slide Images
Abstract
Histopathological examination is a powerful method for the prognosis of critical diseases. But, despite significant
advances in high-speed and high-resolution scanning devices or in virtual exploration capabilities, the clinical analysis
of Whole Slide Images (WSI) largely remains the work of human experts. We propose an innovative platform in which
multi-scale computer vision algorithms perform fast analysis of a histopathological WSI. It relies on specific high and
generic low resolution image analysis algorithms embedded in a multi-scale framework to rapidly identify the high power
fields of interest used by the pathologist to assess a global grading. GPU technologies as well speed up the global
time-efficiency of the system. In a sense, sparse coding and sampling is the keystone of our approach. In terms of
validation, we are designing a computer-aided breast biopsy analysis application based on histopathology images and
designed in collaboration with a pathology department. The current ground truth slides correspond to about 36,000
high magnification (40X) high power fields. The time processing to achieve automatic WSI analysis is on a par with the
pathologist’s performance (about ten minutes a WSI), which constitutes by itself a major contribution of the proposed
methodology.
Pages:14
[thanks-thanks]pdf,1.53MB, http://depositfiles.com/files/80ox7ahaf[/thanks-thanks]
Time-efficient sparse analysis of histopathological Whole Slide Images
Abstract
Histopathological examination is a powerful method for the prognosis of critical diseases. But, despite significant
advances in high-speed and high-resolution scanning devices or in virtual exploration capabilities, the clinical analysis
of Whole Slide Images (WSI) largely remains the work of human experts. We propose an innovative platform in which
multi-scale computer vision algorithms perform fast analysis of a histopathological WSI. It relies on specific high and
generic low resolution image analysis algorithms embedded in a multi-scale framework to rapidly identify the high power
fields of interest used by the pathologist to assess a global grading. GPU technologies as well speed up the global
time-efficiency of the system. In a sense, sparse coding and sampling is the keystone of our approach. In terms of
validation, we are designing a computer-aided breast biopsy analysis application based on histopathology images and
designed in collaboration with a pathology department. The current ground truth slides correspond to about 36,000
high magnification (40X) high power fields. The time processing to achieve automatic WSI analysis is on a par with the
pathologist’s performance (about ten minutes a WSI), which constitutes by itself a major contribution of the proposed
methodology.
Pages:14
[thanks-thanks]pdf,1.53MB, http://depositfiles.com/files/80ox7ahaf[/thanks-thanks]
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