Lung Data Analysis With Deep Learning - Kesavan Vijayakumar, Harikrishnan (Jihočeská univerzita, 2021)
Medical images can have extremely high resolutions which cannot be handled properly by typical stateofart machine learning models. In this thesis, I compared the performance of two approaches of multiple instance learning models where the high resolution images are downscaled into smaller patches and low dimensional embedding are calculated using Resnet. Then low dimensional embedding are aggregated using multiple instance learning to attain class labels. The data set for this thesis consisted of high resolution histological slides of human lung which were classified to contain cancer or not.
Lung Data Analysis With Deep Learning
Keywords: CLAM; Multiple instance learning; Lung data analysis; CLAM; Multiple instance learning; Lung data analysis