Pregled bibliografske jedinice broj: 990778
Hyperspectral imaging for intraoperative diagnosis of colon cancer metastasis in a liver
Hyperspectral imaging for intraoperative diagnosis of colon cancer metastasis in a liver // SPIE Medical Imaging Symposium 2019 - Digital Pathology Conference / Tomaszewski, John ; Ward, Aaron (ur.).
Bellingham (WA): SPIE, 2019. 109560S, 12 doi:10.1117/12.2503907 (poster, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
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Naslov
Hyperspectral imaging for intraoperative diagnosis of colon cancer metastasis in a liver
Autori
Kopriva, Ivica ; Aralica, Gorana ; Popović Hadžija, Marijana ; Hadžija, Mirko ; Dion-Bertrand, Laura-Isabelle ; Chen, Xinjian
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
SPIE Medical Imaging Symposium 2019 - Digital Pathology Conference
/ Tomaszewski, John ; Ward, Aaron - Bellingham (WA) : SPIE, 2019
Skup
SPIE Medical Imaging 2019
Mjesto i datum
San Diego (CA), Sjedinjene Američke Države, 16.02.2019. - 21.02.2019
Vrsta sudjelovanja
Poster
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
intraoperative diagnosis ; hyperspectral microscopic imaging ; liver ; colon cancer metastasis ; spectral angle mapper
Sažetak
Hyperspectral imaging (HSI) is being shown as an emerging modality with a great potential in disease diagnosis and surgical cancer resection. Herein, we evaluate feasibility of the HSI to discriminate and diagnose colon cancer metastasis in a liver from five hematoxylin and eosin stained histopathological specimens. They were collected from the same patient during intraoperative frozen section analysis. Cancer and non-cancer spectra along with corresponding spatial maps were estimated from hyperspectral images by means of spectral unmixing. It was found that maximal angle between cancer spectra is 1.02 degrees less than minimal angle between cancer vs. non-cancer spectra. Thus, spectrum angle mapper was used for pixel-based diagnosis of cancer yielding sensitivity between 81.23% and 97.12%, specificity between 85.85% and 97.3%, and accuracy between 86.85% and 96.92%.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo, Kliničke medicinske znanosti
POVEZANOST RADA
Projekti:
Bilateralni projekta Hrvatska-Kina
HRZZ-IP-2016-06-5235 - Strukturne dekompozicije empirijskih podataka za računalno potpomognutu dijagnostiku bolesti (DEDAD) (Kopriva, Ivica, HRZZ - 2016-06) ( CroRIS)
Ustanove:
Institut "Ruđer Bošković", Zagreb,
Medicinski fakultet, Zagreb,
Klinička bolnica "Dubrava"
Profili:
Mirko Hadžija
(autor)
Marijana Popović-Hadžija
(autor)
Gorana Aralica
(autor)
Ivica Kopriva
(autor)