A hybrid computational pathology method for the detection of perineural invasion junctions

Chang Hee Han; Jin Tae Kwak

doi:10.1117/12.2610756

4 April 2022 A hybrid computational pathology method for the detection of perineural invasion junctions

Chang Hee Han, Jin Tae Kwak

Proceedings Volume 12039, Medical Imaging 2022: Digital and Computational Pathology; 120390X (2022) https://doi.org/10.1117/12.2610756
Event: SPIE Medical Imaging, 2022, San Diego, California, United States

Abstract

Perineural invasion refers to a process where tumor cells invade, surround, or pass through nerve cells, serving as an indicator of aggressive tumor and related to poor prognosis. Herein, we propose an efficient and effective hybrid computational method for an automated detection of perineural invasion junctions in multi-tissue digitized histology images. The proposed approach conducts the detection of perineural invasion junctions in three stages. The first state identifies candidate regions for perineural invasion. The second stage delineates perineural invasion junctions. The last stage eliminates any false positive regions for perineural invasion. In the first two stages, we exploit an advanced deep neural network. In the last stage, we utilize hand-crafted features and a conventional machine learning algorithm. To evaluate the proposed approach, we employ 150 whole slide images obtained from PAIP2021 Challenge: Perineural Invasion in Multiple Organ Cancer and conduct a five-fold cross-validation. The experimental results show that the proposed hybrid approach could facilitate an automated, accurate identification of perineural invasion in histology images.

Conference Presentation

Citation Download Citation

Chang Hee Han and Jin Tae Kwak "A hybrid computational pathology method for the detection of perineural invasion junctions", Proc. SPIE 12039, Medical Imaging 2022: Digital and Computational Pathology, 120390X (4 April 2022); https://doi.org/10.1117/12.2610756

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available