Breast Cancer Classification using Tensorflow
Utilizing a Deep Learning model with Transfer Learning using Inception v3, this project focuses on classifying breast cancer images as benign or malignant. The dataset comprises a total of 105 benign and 50 malignant training images, with a test accuracy of 73.3% and a validation accuracy of 86%. Through this approach, 4 images were correctly classified while 2 were misidentified, showcasing the potential of AI in medical diagnostics.
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Presentation Transcript
Breast Cancer Classification using Tensorflow SYED SHARJEELULLAH
Deep Learning Model Transfer Learning with Inception v3 model An inception v3 model trained on Imagenet images A new top layer has been trained to recognize breast cancer images.
DataSet Classification done between Benign and Malignant Total Benign training set:105 Total Malignant training set:50 Randomly 3 images of each type were used for testing
Model Results Final test Accuracy = 73.3% Validation Accuracy= 86% In the random test 4 images were correctly classified 2 were incorrectly identified
