Enhancing Histopathological Tissue Accuracy Using: OPCNN And BERT

Enhancing Histopathological Tissue Accuracy Using: OPCNN And BERT

Registration ID: IJNRD_201039

Published ID: IJNRD2307078

DOI: Click Here to Get

Swathi s , Dr . K. S. Angel Viji

OPCNN, BERT, Histopathological tissue classification.

Histopathological tissues are not only critical to cancer diagnosis, but they also provide useful tumor microen- vironment information for cancer research. Current CNN classi- fication has already shown strong feature representation ability and promising outcomes for histopathology tissue classification. In this paper, we propose a method using optimized convolutional neural networks (OPCNN) and Bidirectional Encoder Repre- sentations from Transformers (BERT). The convolutional Auto encoder’s aim is to learn an input function to reconstruct the input to an output of fewer dimensions. Tissue Classification is compelled to learn numerical changes that carry the most useful details about the structure of data in order for the deciphering part to operate well in the rebuilding task. The BERT model’s remarkable performance could possibly be attributable to the fact that it is bidirectionally trained. This implies that BERT, which is built on the Transformer model architecture, uses its self- attention mechanism during training to learn information from both the left and right sides, resulting in a deep understanding of the context. On two downstream tasks, picture classification, and semantic segmentation, we fine-tune the pre-trained BERT and self-supervised learning. The output of the BERT layer is routed into OPCNN, which then passes the output to a completely linked bulky layer, which produces a single posture as its final output. On the Lung Colon Cancer Histopathological Image Dataset, we subjected the proposed approach to the test. The findings from the study indicate that the proposed technique can improve tissue-level accuracy for classification by up to 96.91% over time. It significantly shortens the processing time.

Published Paper   E-Certificate

"Enhancing Histopathological Tissue Accuracy Using: OPCNN And BERT", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 7, page no.a622-a627, July-2023, Available :https://ijnrd.org/papers/IJNRD2307078.pdf

Volume 8 Issue 7, July-2023

Pages : a622-a627

Paper Reg. ID: IJNRD_201039

Published Paper Id: IJNRD2307078

Downloads: 000121129

Research Area: Computer Science & Technology 

Country: Kannur , Kerala , India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2307078.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2307078

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

Call For Paper - Volume 10 | Issue 8 | August 2025

IJNRD is Scholarly open access journals, Peer-reviewed, and Refereed Journals, High Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool), Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) with Open-Access Publications.

INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies. The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world. IJNRD will provide an opportunity for practitioners and educators of engineering field to exchange research evidence, models of best practice and innovative ideas.

Indexing In Google Scholar, SSRN, ResearcherID-Publons, Semantic Scholar | AI-Powered Research Tool, Microsoft Academic, Academia.edu, arXiv.org, Research Gate, CiteSeerX, ResearcherID Thomson Reuters, Mendeley : reference manager, DocStoc, ISSUU, Scribd, and many more

How to submit the paper?

Important Dates for Current issue

Paper Submission Open For: August 2025

Current Issue: Volume 10 | Issue 8

Last Date for Paper Submission: Till 31-Aug-2025

Notification of Review Result: Within 1-2 Days after Submitting paper.

Publication of Paper: Within 01-02 Days after Submititng documents.

Frequency: Monthly (12 issue Annually).

Journal Type: International Peer-reviewed, Refereed, and Open Access Journal.

Subject Category: Research Area