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Interpretability of machine intelligence in medical image computing : 5th international workshop, iMIMIC 2022, held in conjunction with MICCAI 2022, Singapore, Singapore, September 22, 2022, proceedings / / edited by Mauricio Reyes, Pedro Henriques Abreu, and Jaime Cardoso
| Interpretability of machine intelligence in medical image computing : 5th international workshop, iMIMIC 2022, held in conjunction with MICCAI 2022, Singapore, Singapore, September 22, 2022, proceedings / / edited by Mauricio Reyes, Pedro Henriques Abreu, and Jaime Cardoso |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (134 pages) |
| Disciplina | 616.0754 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer-assisted surgery
Diagnostic imaging - Data processing |
| ISBN | 3-031-17976-5 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Interpretable Lung Cancer Diagnosis with Nodule Attribute Guidance and Online Model Debugging -- 1 Introduction -- 2 Materials -- 3 Methodology -- 3.1 Collaborative Model Architecture with Attribute-Guidance -- 3.2 Debugging Model with Semantic Interpretation -- 3.3 Explanation by Attribute-Based Nodule Retrieval -- 4 Experiments and Results -- 4.1 Implementation -- 4.2 Quantitative Evaluation -- 4.3 Trustworthiness Check and Interpretable Diagnosis -- 5 Conclusions -- References -- Do Pre-processing and Augmentation Help Explainability? A Multi-seed Analysis for Brain Age Estimation -- 1 Introduction -- 2 Related Work -- 3 Methods -- 4 Results -- 4.1 Performance -- 4.2 Voxel Agreement -- 4.3 Atlas-Based Analyses -- 4.4 Region Validation -- 5 Conclusion -- References -- Towards Self-explainable Transformers for Cell Classification in Flow Cytometry Data -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Architecture -- 3.2 Preprocessing -- 3.3 Loss Function -- 3.4 Data Augmentation -- 4 Experiments -- 4.1 Data -- 4.2 Results -- 5 Conclusion -- References -- Reducing Annotation Need in Self-explanatory Models for Lung Nodule Diagnosis -- 1 Introduction -- 2 Method -- 3 Experimental Results -- 3.1 Prediction Performance of Nodule Attributes and Malignancy -- 3.2 Analysis of Extracted Features in Learned Space -- 3.3 Ablation Study -- 4 Conclusion -- References -- Attention-Based Interpretable Regression of Gene Expression in Histology -- 1 Introduction -- 2 Methods -- 2.1 Datasets -- 2.2 Multiple Instance Regression of Gene Expression -- 2.3 Attention-Based Model Interpretability -- 2.4 Evaluation of Performance and Interpretability -- 3 Experiments and Results -- 3.1 Network Training -- 3.2 Quantitative Model Evaluation -- 3.3 Attention-Based Identification of Hotspots and Patterns.
3.4 Quantitative Evaluation of the Attention -- 4 Discussion -- 5 Conclusion -- A Description of Selected Genes -- B Detailed Model Evaluation -- C Additional Visualizations -- D Single-Cell Co-expression -- References -- Beyond Voxel Prediction Uncertainty: Identifying Brain Lesions You Can Trust -- 1 Introduction -- 2 Our Framework: Graph Modelization for Lesion Uncertainty Quantification -- 2.1 Monte Carlo Dropout Model and Voxel-Wise Uncertainty -- 2.2 Graph Dataset Generation -- 2.3 GCNN Architecture and Training -- 3 Material and Method -- 3.1 Data -- 3.2 Comparison with Known Approaches -- 3.3 Evaluation Setting -- 3.4 Implementation Details -- 4 Results and Discussion -- 5 Conclusion -- References -- Interpretable Vertebral Fracture Diagnosis -- 1 Introduction -- 1.1 Related Work -- 2 Methodology -- 2.1 Vertebral Fracture Detection -- 2.2 Semantic Concept Extraction (Correlation) -- 2.3 Visualization of Highly Correlating Concepts at Inference -- 3 Experimental Setup -- 4 Results and Discussion -- 4.1 Clinical Meaningfulness of Extracted Semantic Concepts -- 4.2 Single-Inference Concept Visualization -- 5 Conclusion -- References -- Multi-modal Volumetric Concept Activation to Explain Detection and Classification of Metastatic Prostate Cancer on PSMA-PET/CT -- 1 Introduction -- 2 Data -- 3 Method -- 3.1 Preprocessing -- 3.2 Detection -- 3.3 Classification -- 3.4 Explainable AI -- 4 Results -- 4.1 Detection -- 4.2 Classification -- 4.3 Explainable AI -- 5 Discussion -- 6 Conclusion -- References -- KAM - A Kernel Attention Module for Emotion Classification with EEG Data -- 1 Introduction -- 2 Related Work -- 3 Kernel Attention Module -- 4 Experiments -- 5 Conclusion -- References -- Explainable Artificial Intelligence for Breast Tumour Classification: Helpful or Harmful -- 1 Introduction -- 2 Related Work -- 2.1 XAI in Medicine. 3 Model Setup -- 3.1 Data Pre-Processing -- 3.2 Model Architecture -- 4 Explanations -- 4.1 LIME -- 4.2 RISE -- 4.3 SHAP -- 5 Evaluating Explanations -- 5.1 One-Way ANOVA -- 5.2 Kendall's Tau -- 5.3 Radiologist Evaluation -- 5.4 Threats to Validity -- 6 Observations and Discussion -- 6.1 Discussion -- A Appendix -- A.1 Model Training Results -- A.2 Choosing L Parameter for LIME -- A.3 One-Way ANOVA Results -- A.4 Pixel Agreement Statistics -- A.5 Ranked Biased Overlap (RBO) Results -- A.6 Kendall's Tau Results -- A.7 Radiologist Opinions -- A.8 Explanation Examples -- References -- Author Index. |
| Record Nr. | UNISA-996495570803316 |
| Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Interpretability of machine intelligence in medical image computing : 5th international workshop, iMIMIC 2022, held in conjunction with MICCAI 2022, Singapore, Singapore, September 22, 2022, proceedings / / edited by Mauricio Reyes, Pedro Henriques Abreu, and Jaime Cardoso
| Interpretability of machine intelligence in medical image computing : 5th international workshop, iMIMIC 2022, held in conjunction with MICCAI 2022, Singapore, Singapore, September 22, 2022, proceedings / / edited by Mauricio Reyes, Pedro Henriques Abreu, and Jaime Cardoso |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (134 pages) |
| Disciplina | 616.0754 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer-assisted surgery
Diagnostic imaging - Data processing |
| ISBN | 3-031-17976-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Interpretable Lung Cancer Diagnosis with Nodule Attribute Guidance and Online Model Debugging -- 1 Introduction -- 2 Materials -- 3 Methodology -- 3.1 Collaborative Model Architecture with Attribute-Guidance -- 3.2 Debugging Model with Semantic Interpretation -- 3.3 Explanation by Attribute-Based Nodule Retrieval -- 4 Experiments and Results -- 4.1 Implementation -- 4.2 Quantitative Evaluation -- 4.3 Trustworthiness Check and Interpretable Diagnosis -- 5 Conclusions -- References -- Do Pre-processing and Augmentation Help Explainability? A Multi-seed Analysis for Brain Age Estimation -- 1 Introduction -- 2 Related Work -- 3 Methods -- 4 Results -- 4.1 Performance -- 4.2 Voxel Agreement -- 4.3 Atlas-Based Analyses -- 4.4 Region Validation -- 5 Conclusion -- References -- Towards Self-explainable Transformers for Cell Classification in Flow Cytometry Data -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Architecture -- 3.2 Preprocessing -- 3.3 Loss Function -- 3.4 Data Augmentation -- 4 Experiments -- 4.1 Data -- 4.2 Results -- 5 Conclusion -- References -- Reducing Annotation Need in Self-explanatory Models for Lung Nodule Diagnosis -- 1 Introduction -- 2 Method -- 3 Experimental Results -- 3.1 Prediction Performance of Nodule Attributes and Malignancy -- 3.2 Analysis of Extracted Features in Learned Space -- 3.3 Ablation Study -- 4 Conclusion -- References -- Attention-Based Interpretable Regression of Gene Expression in Histology -- 1 Introduction -- 2 Methods -- 2.1 Datasets -- 2.2 Multiple Instance Regression of Gene Expression -- 2.3 Attention-Based Model Interpretability -- 2.4 Evaluation of Performance and Interpretability -- 3 Experiments and Results -- 3.1 Network Training -- 3.2 Quantitative Model Evaluation -- 3.3 Attention-Based Identification of Hotspots and Patterns.
3.4 Quantitative Evaluation of the Attention -- 4 Discussion -- 5 Conclusion -- A Description of Selected Genes -- B Detailed Model Evaluation -- C Additional Visualizations -- D Single-Cell Co-expression -- References -- Beyond Voxel Prediction Uncertainty: Identifying Brain Lesions You Can Trust -- 1 Introduction -- 2 Our Framework: Graph Modelization for Lesion Uncertainty Quantification -- 2.1 Monte Carlo Dropout Model and Voxel-Wise Uncertainty -- 2.2 Graph Dataset Generation -- 2.3 GCNN Architecture and Training -- 3 Material and Method -- 3.1 Data -- 3.2 Comparison with Known Approaches -- 3.3 Evaluation Setting -- 3.4 Implementation Details -- 4 Results and Discussion -- 5 Conclusion -- References -- Interpretable Vertebral Fracture Diagnosis -- 1 Introduction -- 1.1 Related Work -- 2 Methodology -- 2.1 Vertebral Fracture Detection -- 2.2 Semantic Concept Extraction (Correlation) -- 2.3 Visualization of Highly Correlating Concepts at Inference -- 3 Experimental Setup -- 4 Results and Discussion -- 4.1 Clinical Meaningfulness of Extracted Semantic Concepts -- 4.2 Single-Inference Concept Visualization -- 5 Conclusion -- References -- Multi-modal Volumetric Concept Activation to Explain Detection and Classification of Metastatic Prostate Cancer on PSMA-PET/CT -- 1 Introduction -- 2 Data -- 3 Method -- 3.1 Preprocessing -- 3.2 Detection -- 3.3 Classification -- 3.4 Explainable AI -- 4 Results -- 4.1 Detection -- 4.2 Classification -- 4.3 Explainable AI -- 5 Discussion -- 6 Conclusion -- References -- KAM - A Kernel Attention Module for Emotion Classification with EEG Data -- 1 Introduction -- 2 Related Work -- 3 Kernel Attention Module -- 4 Experiments -- 5 Conclusion -- References -- Explainable Artificial Intelligence for Breast Tumour Classification: Helpful or Harmful -- 1 Introduction -- 2 Related Work -- 2.1 XAI in Medicine. 3 Model Setup -- 3.1 Data Pre-Processing -- 3.2 Model Architecture -- 4 Explanations -- 4.1 LIME -- 4.2 RISE -- 4.3 SHAP -- 5 Evaluating Explanations -- 5.1 One-Way ANOVA -- 5.2 Kendall's Tau -- 5.3 Radiologist Evaluation -- 5.4 Threats to Validity -- 6 Observations and Discussion -- 6.1 Discussion -- A Appendix -- A.1 Model Training Results -- A.2 Choosing L Parameter for LIME -- A.3 One-Way ANOVA Results -- A.4 Pixel Agreement Statistics -- A.5 Ranked Biased Overlap (RBO) Results -- A.6 Kendall's Tau Results -- A.7 Radiologist Opinions -- A.8 Explanation Examples -- References -- Author Index. |
| Record Nr. | UNINA-9910616374003321 |
| Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part III / / edited by Albert Bifet, Michael May, Bianca Zadrozny, Ricard Gavalda, Dino Pedreschi, Francesco Bonchi, Jaime Cardoso, Myra Spiliopoulou
| Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part III / / edited by Albert Bifet, Michael May, Bianca Zadrozny, Ricard Gavalda, Dino Pedreschi, Francesco Bonchi, Jaime Cardoso, Myra Spiliopoulou |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (XXX, 345 p. 122 illus.) |
| Disciplina | 006.31 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Data mining
Artificial intelligence Pattern recognition Information storage and retrieval Database management Application software Data Mining and Knowledge Discovery Artificial Intelligence Pattern Recognition Information Storage and Retrieval Database Management Information Systems Applications (incl. Internet) |
| ISBN | 3-319-23461-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996200360203316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part III / / edited by Albert Bifet, Michael May, Bianca Zadrozny, Ricard Gavalda, Dino Pedreschi, Francesco Bonchi, Jaime Cardoso, Myra Spiliopoulou
| Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part III / / edited by Albert Bifet, Michael May, Bianca Zadrozny, Ricard Gavalda, Dino Pedreschi, Francesco Bonchi, Jaime Cardoso, Myra Spiliopoulou |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (XXX, 345 p. 122 illus.) |
| Disciplina | 006.31 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Data mining
Artificial intelligence Pattern recognition Information storage and retrieval Database management Application software Data Mining and Knowledge Discovery Artificial Intelligence Pattern Recognition Information Storage and Retrieval Database Management Information Systems Applications (incl. Internet) |
| ISBN | 3-319-23461-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910483879403321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Pattern Recognition and Image Analysis [[electronic resource] ] : 6th Iberian Conference, IbPRIA 2013, Funchal, Madeira, Portugal, June 5-7, 2013, Proceedings / / edited by Joao Miguel Sanches, Luisa Micó, Jaime Cardoso
| Pattern Recognition and Image Analysis [[electronic resource] ] : 6th Iberian Conference, IbPRIA 2013, Funchal, Madeira, Portugal, June 5-7, 2013, Proceedings / / edited by Joao Miguel Sanches, Luisa Micó, Jaime Cardoso |
| Edizione | [1st ed. 2013.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2013 |
| Descrizione fisica | 1 online resource (XX, 900 p. 396 illus.) |
| Disciplina | 006.42 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Pattern recognition
Optical data processing Natural language processing (Computer science) Computer graphics Artificial intelligence Pattern Recognition Computer Imaging, Vision, Pattern Recognition and Graphics Image Processing and Computer Vision Natural Language Processing (NLP) Computer Graphics Artificial Intelligence |
| ISBN | 3-642-38628-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Computer vision -- Pattern recognition -- Image and signal -- Application. |
| Record Nr. | UNISA-996466305503316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Pattern Recognition and Image Analysis : 6th Iberian Conference, IbPRIA 2013, Funchal, Madeira, Portugal, June 5-7, 2013, Proceedings / / edited by Joao Miguel Sanches, Luisa Micó, Jaime Cardoso
| Pattern Recognition and Image Analysis : 6th Iberian Conference, IbPRIA 2013, Funchal, Madeira, Portugal, June 5-7, 2013, Proceedings / / edited by Joao Miguel Sanches, Luisa Micó, Jaime Cardoso |
| Edizione | [1st ed. 2013.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2013 |
| Descrizione fisica | 1 online resource (XX, 900 p. 396 illus.) |
| Disciplina | 006.42 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Pattern recognition
Optical data processing Natural language processing (Computer science) Computer graphics Artificial intelligence Pattern Recognition Computer Imaging, Vision, Pattern Recognition and Graphics Image Processing and Computer Vision Natural Language Processing (NLP) Computer Graphics Artificial Intelligence |
| ISBN | 3-642-38628-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Computer vision -- Pattern recognition -- Image and signal -- Application. |
| Record Nr. | UNINA-9910482995403321 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||