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Offset-Sparsity Decomposition for Enhancement of Color Microscopic Image of Stained Specimen in Histopathology: Further Results (CROSBI ID 633864)

Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija

Kopriva, Ivica ; Popović Hadžija Marijana ; Hadžija Mirko ; Aralica Gorana Offset-Sparsity Decomposition for Enhancement of Color Microscopic Image of Stained Specimen in Histopathology: Further Results // Proceedings of the SPIE vol. 9791 / Gurcan, Metin K ; Madabhushi A (ur.). Bellingham (WA): SPIE, 2016. str. 97910P-1-97910P-8

Podaci o odgovornosti

Kopriva, Ivica ; Popović Hadžija Marijana ; Hadžija Mirko ; Aralica Gorana

engleski

Offset-Sparsity Decomposition for Enhancement of Color Microscopic Image of Stained Specimen in Histopathology: Further Results

Recently, novel data-driven offset-sparsity decomposition (OSD) method was proposed by us to increase colorimetric difference between tissue-structures present in the color microscopic image of stained specimen in histopathology. The OSD method performs additive decomposition of vectorized spectral images into image-adapted offset term and sparse term. Thereby, the sparse term represents an enhanced image. The method was tested on images of the histological slides of human liver stained with hematoxylin and eosin, anti-CD34 monoclonal antibody and Sudan III. Herein, we present further results related to increase of colorimetric difference between tissue structures present in the images of human liver specimens with pancreatic carcinoma metastasis stained with Gomori, CK7, CDX2 and LCA, and with colon carcinoma metastasis stained with Gomori, CK20 and PAN CK. Obtained relative increase of colorimetric difference is in the range [19.36%, 103.94%].

Histopatological image enhancement ; colorimetric difference ; offset-sparisty decomposition

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Podaci o prilogu

97910P-1-97910P-8.

2016.

objavljeno

Podaci o matičnoj publikaciji

Proceedings of the SPIE vol. 9791

Gurcan, Metin K ; Madabhushi A

Bellingham (WA): SPIE

Podaci o skupu

Medical Imaging Symposium 2016 - Digital Pathology Conference

predavanje

27.02.2016-03.03.2016

San Diego (CA), Sjedinjene Američke Države

Povezanost rada

Matematika, Računarstvo, Kliničke medicinske znanosti