Automatic extraction of cell nuclei from H&E-stained histopathological images.

Faliu Yi,Guanghua Xiao,Junzhou Huang,Yang Xie,Lin Yang

doi:10.1117/1.jmi.4.2.027502

Abstract

.Extraction of cell nuclei from hematoxylin and eosin (H&E)-stained histopathological images is an essential preprocessing step in computerized image analysis for disease detection, diagnosis, and prognosis. We present an automated cell nuclei segmentation approach that works with H&E-stained images. A color deconvolution algorithm was first applied to the image to get the hematoxylin channel. Using a morphological operation and thresholding technique on the hematoxylin channel image, candidate target nuclei and background regions were detected, which were then used as markers for a marker-controlled watershed transform segmentation algorithm. Moreover, postprocessing was conducted to split the touching nuclei. For each segmented region from the previous steps, the regional maximum value positions were identified as potential nuclei centers. These maximum values were further grouped into -clusters, and the locations within each cluster were connected with the minimum spanning tree technique. Then, these connected positions were utilized as new markers for a watershed segmentation approach. The final number of nuclei at each region was determined by minimizing an objective function that iterated all of the possible -values. The proposed method was applied to the pathological images of the tumor tissues from The Cancer Genome Atlas study. Experimental results show that the proposed method can lead to promising results in terms of segmentation accuracy and separation of touching nuclei.

Highlights

With the advent of fast digital slide scanners, tissue histopathology slides are able to be digitized and stored in a digital image form that can be repeatedly accessed and examined by pathologists.[1,2,3,4,5] In practice, different components of the tissue are dyed with different stains so that the specific tissue components can be differentiated in digital histopathology images, to facilitate visual inspection by pathologists
10 Hematoxylin and eosin (H&E)-stained histopathological slide images with lung cancer were randomly selected from The Cancer Genome Atlas (TCGA) dataset
We developed an automatic method that is able to segment cell nuclei in H&E-stained histopathological images

Summary

Introduction

With the advent of fast digital slide scanners, tissue histopathology slides are able to be digitized and stored in a digital image form that can be repeatedly accessed and examined by pathologists.[1,2,3,4,5] In practice, different components of the tissue are dyed with different stains so that the specific tissue components can be differentiated in digital histopathology images, to facilitate visual inspection by pathologists. Hematoxylin and eosin (H&E) staining is a widespread staining protocol and has been widely used in pathological staining. Hematoxylin stains the nuclei in a dark blue color while eosin stains cytoplasm as pink,[5] which enables morphological feature analysis related to cell nuclei. Pathological examination, in which a series of H&E-stained histopathological slides are manually examined by pathologists for disease diagnosis, is a time-consuming and labor-intensive task. This process is subjective, prone to error, and has large inter- and intraobserver variation. Due to the heterogeneity and morphological complexity of tumors, it is a challenging task even for well-trained pathologists to reach an agreement when diagnosing a tumor sample by visual

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Conclusion