DEEP LEARNING APPROACHES TO CHRONIC VENOUS DISEASE CLASSIFICATION

DEEP LEARNING APPROACHES TO CHRONIC VENOUS DISEASE CLASSIFICATION

Registration ID: IJNRD_220519

Published ID: IJNRD2405067

DOI: Click Here to Get

Akshata Dattatray Desai , Rutika Vijay Katkar , Arati Dipak Patil , Nikita Ananda Lengare

Chronic venous disease classification using image, Varicose veins detection, CVD detection using machine learning.

Chronic venous Disease is a disease that affects the more number of people across the world especially in women due to stress and work life. Avoiding the symptoms of varicose veins may occur severe problem. So, the main aim of the work is the self diagnosis of chronic venous Disease(CVD) at early stage in the patient with the help of images. We have used the machine learning concept to reach towards our aim and complete the work. The datasets are collected from the GitHub site and classified into five stages(normal skin , reticular skin , varicose vein , pigmentation and venous ulcer).The convolution neural network algorithm is used to train the model. CNN has different layers as Image input layer, Convolution 2d layer, Batch normalization layer, Rectified Linear unit layer, Max-pooling 2d layer, Fully connected layer and Soft-max layer. The datasets are splitted into training data and testing data. After the training we get Loss and Accuracy graph which decides whether the model is ready for real time application or not. With the help of GUI we have created the different buttons(Preprocess button , Train Test Split button , Train Data button , Analysis and Test button , Save Model button , Load Model button , Select Image button , Select Image button , Show Image button and Predict button). When training is completed , the analysis and testing is done. In the testing unseen data is taken to see how model is performing on new data. After testing the model is save and load. In the validation the new image is selected , then the image is shown on the screen and at last the result is observed that in which classification the image belongs to. Here , the evaluation is done more accurately.

Published Paper   E-Certificate

"DEEP LEARNING APPROACHES TO CHRONIC VENOUS DISEASE CLASSIFICATION", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 5, page no.a643-a651, May-2024, Available :https://ijnrd.org/papers/IJNRD2405067.pdf

Volume 9 Issue 5, May-2024

Pages : a643-a651

Paper Reg. ID: IJNRD_220519

Published Paper Id: IJNRD2405067

Downloads: 000121129

Research Area: Electronics & Communication Engg. 

Country: Kolhapur, Maharashtra, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2405067.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2405067

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

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