Malignancy Detection in Lung and Colon Histopathology Images Using Transfer Learning with Class-Selective Image Processing
Author(s):
S.P.Mahima, S.Vidhya Lakshmi, S.Jaipreetha, S.Kaviya Linga Shree
Keywords:
Feature Extraction, Transfer Learning Class-Selective Image Processing, Image Segmentation.
Abstract
Lung and colon Cancer could be a Disease of uncontrolled cell growth in tissues of the lung. Discovery of carcinoma in its initial stage is that the key of its cure. All in all, a measure for earlier than schedule stage lung disease determination essentially incorporates those using Histopathology images. In numerous countries collecting Histopathology images isn't yet pragmatic. So, we'll utilize some systems are key to image dataset of medicinal picture mining, Lung Field collection, processing, Feature Extraction classification utilizing transfer learning algorithm of Vgg16, the power of deep learning, to address the challenges of early- stage detection in two critical types of cancer lung and colon. By using large-scale medical imaging datasets, the VGG16 model is trained to recognize subtle patterns. Our approach seeks to provide a robust and automated tool for identifying potential malignancies at their incipient stages. The fusion of cutting-edge technology with medical expertise underscores our commitment to advancing healthcare and enhancing the prospects of early cancer detection.
Article Details
Unique Paper ID: 164067

Publication Volume & Issue: Volume 10, Issue 12

Page(s): 226 - 232
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