Influence based explainability of brain tumors segmentation in
multimodal Magnetic Resonance Imaging

Influence based explainability of brain tumors segmentation in multimodal Magnetic Resonance Imaging

5 April 2024

Andrea Ciardiello

Simona Gargiulo

Simone Scardapane

ArXiv (abs)PDF HTML

Papers citing "Influence based explainability of brain tumors segmentation in multimodal Magnetic Resonance Imaging"

19 / 19 papers shown

Title
Beyond Explaining: Opportunities and Challenges of XAI-Based Model Improvement Leander Weber Sebastian Lapuschkin Alexander Binder Wojciech Samek 97 100 0 15 Mar 2022
Evaluating Explainable AI on a Multi-Modal Medical Imaging Task: Can Existing Algorithms Fulfill Clinical Requirements? Weina Jin Xiaoxiao Li Ghassan Hamarneh 50 52 0 12 Mar 2022
From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI Meike Nauta Jan Trienes Shreyasi Pathak Elisa Nguyen Michelle Peters Yasmin Schmitt Jorg Schlotterer M. V. Keulen C. Seifert ELM XAI 151 418 0 20 Jan 2022
Explainable AI (XAI): A Systematic Meta-Survey of Current Challenges and Future Opportunities Waddah Saeed C. Omlin XAI 88 442 0 11 Nov 2021
Explainable artificial intelligence (XAI) in deep learning-based medical image analysis Bas H. M. van der Velden Hugo J. Kuijf K. Gilhuijs M. Viergever XAI 101 667 0 22 Jul 2021
One Map Does Not Fit All: Evaluating Saliency Map Explanation on Multi-Modal Medical Images Weina Jin Xiaoxiao Li Ghassan Hamarneh FAtt 45 16 0 11 Jul 2021
On the Sensitivity and Stability of Model Interpretations in NLP Fan Yin Zhouxing Shi Cho-Jui Hsieh Kai-Wei Chang FAtt 68 33 0 18 Apr 2021
Reviewing the Need for Explainable Artificial Intelligence (xAI) Julie Gerlings Arisa Shollo Ioanna D. Constantiou 55 73 0 02 Dec 2020
The role of explainability in creating trustworthy artificial intelligence for health care: a comprehensive survey of the terminology, design choices, and evaluation strategies A. Markus J. Kors P. Rijnbeek 87 468 0 31 Jul 2020
RelatIF: Identifying Explanatory Training Examples via Relative Influence Elnaz Barshan Marc-Etienne Brunet Gintare Karolina Dziugaite TDI 133 30 0 25 Mar 2020
Estimating Training Data Influence by Tracing Gradient Descent G. Pruthi Frederick Liu Mukund Sundararajan Satyen Kale TDI 108 419 0 19 Feb 2020
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI Alejandro Barredo Arrieta Natalia Díaz Rodríguez Javier Del Ser Adrien Bennetot Siham Tabik ... S. Gil-Lopez Daniel Molina Richard Benjamins Raja Chatila Francisco Herrera XAI 130 6,321 0 22 Oct 2019
Demystifying Brain Tumour Segmentation Networks: Interpretability and Uncertainty Analysis Parth Natekar Avinash Kori Ganapathy Krishnamurthi 46 1 0 03 Sep 2019
How model accuracy and explanation fidelity influence user trust A. Papenmeier G. Englebienne C. Seifert FaML 52 110 0 26 Jul 2019
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge Spyridon Bakas M. Reyes Andras Jakab Stefan Bauer Markus Rempfler ... Jayashree Kalpathy-Cramer Keyvan Farahani Christos Davatzikos Koen van Leemput Bjoern Menze 141 1,639 0 05 Nov 2018
Sanity Checks for Saliency Maps Julius Adebayo Justin Gilmer M. Muelly Ian Goodfellow Moritz Hardt Been Kim FAtt AAML XAI 152 1,970 0 08 Oct 2018
A Benchmark for Interpretability Methods in Deep Neural Networks Sara Hooker D. Erhan Pieter-Jan Kindermans Been Kim FAtt UQCV 125 683 0 28 Jun 2018
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 1.9K 77,441 0 18 May 2015
Rich feature hierarchies for accurate object detection and semantic segmentation Ross B. Girshick Jeff Donahue Trevor Darrell Jitendra Malik ObjD 295 26,223 0 11 Nov 2013

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