A Framework for Falsifiable Explanations of Machine Learning Models with an Application in Computational Pathology

In recent years, deep learning has been the key driver of breakthrough developments in computational pathology and other image based approaches that support medical diagnosis and treatment. The underlying neural networks as inherent black boxes lack transparency, and are often accompanied by approaches to explain their output. However, formally defining explainability has been a notorious unsolved riddle. Here, we introduce a hypothesis-based framework for falsifiable explanations of machine learning models. A falsifiable explanation is a hypothesis that connects an intermediate space induced by the model with the sample from which the data originate. We instantiate this framework in a computational pathology setting using label-free infrared microscopy. The intermediate space is an activation map, which is trained with an inductive bias to localize tumor. An explanation is constituted by hypothesizing that activation corresponds to tumor and associated structures, which we validate by histological staining as an independent secondary experiment.

An Automated Brain Tumor Detection in MRI using Firefly Optimized Segmentation

In the medical field brain tumor detection is an important application. The existing techniques of segmentation has various limitations. Existing techniques ignored the medical images which have poor quality or low brightness. Segmentation becomes the challenging issue as the image contains non-uniform object texture, cluttered objects, different image content and image noise. New technique of segmentation is proposed by research to detect tumor from MR images using firefly algorithm, then tumor is segmented and its features are extracted from MR image. The main goal of Research to design an algorithm for MRI based brain tumor segmentation using firefly algorithm and to improve the accuracy of the tumor detection. Fireflies produce a reaction in their body which produce light , this chemical reaction is called bioluminescent. By using firefly technique it is possible to detect and localize tumor accurately. For comparative analysis, various parameters are used to demonstrate the superiority of proposed method over the conventional ones.