Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Log-Base2 of Gaussian Kernel for Nuclei Segmentation from Colorectal Cancer H and E-Stained Histopathology Images Subject The topic of the resource Canny edge detection; Gaussian filter; Histopathology Images; Laplacian of Gaussian (LoG); Logarithm Base-2 of Gaussian (Log-Base2-G) Kernel; Nuclei Segmentation Description An account of the resource Nuclei Segmentation is a very essential and intermediate step for automatic cancer detection from H and E stained histopathology images. In the recent advent, the rise of Convolutional Neural Network (CNN), has enabled researchers to detect nuclei automatically from histopathology images with higher accuracy. However, the performance of automatic nuclei segmentation by CNN is fraught with overfitting, due to very less number of annotated segmented images available. Indeed, we find that the problem of nuclei segmentation is an unsupervised problem, because still now there is no automatic tool available which can make annotated images (nuclei segmented images) accurately, to the best of our knowledge. In this research article, we present a Logarithmic-Base2 of Gaussian (Log-Base2-G) Kernel which has the ability to track only the nuclei portions automatically from Colorectal Cancer H and E stained histopathology images. First, Log-Base2-G Kernel is applied to the input images. Thereafter, we apply an adaptive Canny Edge detector, in order to segment only the nuclei edges from H and E stained histopathology images. Experimental results revealed that our proposed method achieved higher accuracy and F1 score, without the help of any annotated data which is a significant improvement. We have used two different datasets (Con-SeP dataset, and Glass-contest dataset, both contains Colorectal Cancer histopathology images) to check the effectiveness and validity of our proposed method. These results have shown that our proposed method outperformed other image processing or unsupervised methods both qualitatively and quantitatively. 2023 SPIE. Creator An entity primarily responsible for making the resource Roy S.; Khurana R.; Jain V. Source A related resource from which the described resource is derived Proceedings of SPIE - The International Society for Optical Engineering, Vol-12701 Publisher An entity responsible for making the resource available SPIE Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1117/12.2679250" target="_blank" rel="noreferrer noopener">https://doi.org/10.1117/12.2679250</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85172915740&amp;doi=10.1117%2F12.2679250&amp;partnerID=40&amp;md5=fdaaf59ef50507eb4cfe77cfb8821833" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85172915740&amp;doi=10.1117%2f12.2679250&amp;partnerID=40&amp;md5=fdaaf59ef50507eb4cfe77cfb8821833</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 0277786X; ISBN: 978-151066618-4; CODEN: PSISD Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Roy S., School of Engineering and Technology, Christ (Deemed to be University), Bangalore, India; Khurana R., Department of Computer Science and Engineering, Bharati Vidyapeeths College of Engineering, New Delhi, India; Jain V., School of Computer Science, Engineering and Technology, Bennett University, Greater Noida, India