Multi-scale local explanation approach for image analysis using model-agnostic Explainable Artificial Intelligence (XAI)

Hooria Hajiyan; Mehran Ebrahimi

doi:10.1117/12.2654307

6 April 2023 Multi-scale local explanation approach for image analysis using model-agnostic Explainable Artificial Intelligence (XAI)

Hooria Hajiyan, Mehran Ebrahimi

Author Affiliations +

Proceedings Volume 12471, Medical Imaging 2023: Digital and Computational Pathology; 124711N (2023) https://doi.org/10.1117/12.2654307
Event: SPIE Medical Imaging, 2023, San Diego, California, United States

Conference Poster

Abstract

The recent success of deep neural networks has generated remarkable growth in Artificial Intelligence (AI) research and has received much interest over the past few years. One of the main challenges for the broad adoption of deep learning-based models such as Convolutional Neural Networks (CNN) is the lack of understanding of their decisions. To address this issue, Explainable Artificial Intelligence (XAI) has been proposed to shift toward more transparent AI, resulting in the development of techniques to explain decisions by AI models. This paper aims to explore and develop a multi-scale scheme of LIME (Local Interpretable Model-Agnostic Explanations) applied to image classification to explain decisions made by CNN models through heatmaps of coarse to finer scales. More precisely, when LIME highlights large superpixels from a coarse scale, there may be smaller regions in the corresponding superpixel that influenced the model’s prediction at some finer scale. In the proposed multi-scale scheme, two weighting approaches, one based on Gaussian distribution and another parameter-free framework will be introduced to produce visual explanations observed from different scales. Promising results for multi-scale classification heatmaps of histopathology images are presented. More specifically, we investigated the proposed multi-scale approach on Camelyon16 dataset. The results show that the explanations are faithful to the underlying model, and the visualizations are reasonably interpretable.

Citation Download Citation

Hooria Hajiyan and Mehran Ebrahimi "Multi-scale local explanation approach for image analysis using model-agnostic Explainable Artificial Intelligence (XAI)", Proc. SPIE 12471, Medical Imaging 2023: Digital and Computational Pathology, 124711N (6 April 2023); https://doi.org/10.1117/12.2654307

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