Yıl 2020, Cilt 23 , Sayı 1, Sayfalar 7 - 17 2020-03-01

A Novel Probabilistic Nuclei Segmentation Algorithm for H&E Stained Histopathological Tissue Images
A Novel Probabilistic Nuclei Segmentation Algorithm for H&E Stained Histopathological Tissue Images

Faruk SERİN [1] , Metin ERTÜRKLER [2] , Mehmet GÜL [3]


In this study, we propose a novel, fast and accurate segmentation algorithm to segment nuclei in H&E stained histopathological tissue images. The proposed algorithm doesn’t require pre-processing, post-processing, and any manual parameter or threshold. The algorithm utilizes probabilistic and statistical properties of the pixels’ color value in the images with RGB color, and determines whether pixels are a part of any nuclei or not by using an automatically calculated threshold value. The algorithm provides time efficiency and reduced overall cost in the segmentation. The other contributions of the study are false positive removal algorithm and automatically determination of nuclei cluster for K-means. In order to compare and evaluate the performance of the proposed algorithm in terms of time and cost efficiency, K-Means is preferred because of its common usage. Expert evaluation is declared as ground truth for determining the accuracy of the results. The experiments are performed on 60 healthy and 60 damaged kidney, and 60 healthy and 60 damaged liver tissue images. The evaluations are revealed that the proposed algorithm can effectively segment nuclei. The comparison results also demonstrate that the deviation between proposed algorithm and the expert is 2%, while the deviation between K-Means and Expert is 5%.

In this study, we propose a novel, fast and accurate segmentation algorithm to segment nuclei in H&E stained histopathological tissue images. The proposed algorithm does not require pre-processing, post-processing, and any manual parameter or threshold. The algorithm utilizes probabilistic and statistical properties of the pixels’ color value in the images with RGB color space, and determines whether pixels are a part of any nuclei or not by using an automatically calculated threshold value. The algorithm provides time efficiency and reduced overall cost in the segmentation. Two more algorithms are also proposed to distinguish nuclei cluster from the other clusters obtained by K-means, and eliminate false positives in nuclei cluster, which are not nuclei. In order to compare and evaluate the performance of the proposed segmentation algorithm in terms of time and cost efficiency, K-Means is preferred because of its common usage. Expert evaluation is declared as ground truth for determining the accuracy of the results. The experiments are performed on 60 healthy and 60 damaged kidney, and 60 healthy and 60 damaged liver tissue images. The evaluations show that the proposed algorithm can effectively segment nuclei. The comparison results also demonstrate that the deviation between proposed algorithm and the expert is 2%, while the deviation between K-Means and expert is 5%.

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Birincil Dil en
Konular Mühendislik
Bölüm Araştırma Makalesi
Yazarlar

Orcid: 0000-0002-1458-4508
Yazar: Faruk SERİN (Sorumlu Yazar)
Kurum: MUNZUR UNIVERSITY
Ülke: Turkey


Orcid: 0000-0000-0000-0000
Yazar: Metin ERTÜRKLER
Kurum: INONU UNIVERSITY
Ülke: Turkey


Yazar: Mehmet GÜL

Tarihler

Yayımlanma Tarihi : 1 Mart 2020

Bibtex @araştırma makalesi { politeknik464541, journal = {Politeknik Dergisi}, issn = {}, eissn = {2147-9429}, address = {Gazi Üniversitesi Teknoloji Fakültesi 06500 Teknikokullar - ANKARA}, publisher = {Gazi Üniversitesi}, year = {2020}, volume = {23}, pages = {7 - 17}, doi = {10.2339/politeknik.464541}, title = {A Novel Probabilistic Nuclei Segmentation Algorithm for H\&E Stained Histopathological Tissue Images}, key = {cite}, author = {SERİN, Faruk and ERTÜRKLER, Metin and GÜL, Mehmet} }
APA SERİN, F , ERTÜRKLER, M , GÜL, M . (2020). A Novel Probabilistic Nuclei Segmentation Algorithm for H&E Stained Histopathological Tissue Images. Politeknik Dergisi , 23 (1) , 7-17 . DOI: 10.2339/politeknik.464541
MLA SERİN, F , ERTÜRKLER, M , GÜL, M . "A Novel Probabilistic Nuclei Segmentation Algorithm for H&E Stained Histopathological Tissue Images". Politeknik Dergisi 23 (2020 ): 7-17 <https://dergipark.org.tr/tr/pub/politeknik/issue/51707/464541>
Chicago SERİN, F , ERTÜRKLER, M , GÜL, M . "A Novel Probabilistic Nuclei Segmentation Algorithm for H&E Stained Histopathological Tissue Images". Politeknik Dergisi 23 (2020 ): 7-17
RIS TY - JOUR T1 - A Novel Probabilistic Nuclei Segmentation Algorithm for H&E Stained Histopathological Tissue Images AU - Faruk SERİN , Metin ERTÜRKLER , Mehmet GÜL Y1 - 2020 PY - 2020 N1 - doi: 10.2339/politeknik.464541 DO - 10.2339/politeknik.464541 T2 - Politeknik Dergisi JF - Journal JO - JOR SP - 7 EP - 17 VL - 23 IS - 1 SN - -2147-9429 M3 - doi: 10.2339/politeknik.464541 UR - https://doi.org/10.2339/politeknik.464541 Y2 - 2019 ER -
EndNote %0 Politeknik Dergisi A Novel Probabilistic Nuclei Segmentation Algorithm for H&E Stained Histopathological Tissue Images %A Faruk SERİN , Metin ERTÜRKLER , Mehmet GÜL %T A Novel Probabilistic Nuclei Segmentation Algorithm for H&E Stained Histopathological Tissue Images %D 2020 %J Politeknik Dergisi %P -2147-9429 %V 23 %N 1 %R doi: 10.2339/politeknik.464541 %U 10.2339/politeknik.464541
ISNAD SERİN, Faruk , ERTÜRKLER, Metin , GÜL, Mehmet . "A Novel Probabilistic Nuclei Segmentation Algorithm for H&E Stained Histopathological Tissue Images". Politeknik Dergisi 23 / 1 (Mart 2020): 7-17 . https://doi.org/10.2339/politeknik.464541
AMA SERİN F , ERTÜRKLER M , GÜL M . A Novel Probabilistic Nuclei Segmentation Algorithm for H&E Stained Histopathological Tissue Images. Politeknik Dergisi. 2020; 23(1): 7-17.
Vancouver SERİN F , ERTÜRKLER M , GÜL M . A Novel Probabilistic Nuclei Segmentation Algorithm for H&E Stained Histopathological Tissue Images. Politeknik Dergisi. 2020; 23(1): 17-7.