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Evis Sala
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2020 – today
- 2024
- [c4]Inês Prata Machado, Anna Reithmeir, Fryderyk Victor Kögl, Leonardo Rundo, Gabriel Funingana, Marika Reinius, Gift Mungmeeprued, Zeyu Gao, Cathal McCague, Eric Kerfoot, Ramona Woitek, Evis Sala, Yangming Ou, James D. Brenton, Julia A. Schnabel, Mireia Crispin:
A Self-supervised Image Registration Approach for Measuring Local Response Patterns in Metastatic Ovarian Cancer. WBIR 2024: 295-307 - [i12]Inês Prata Machado, Anna Reithmeir, Fryderyk Victor Kögl, Leonardo Rundo, Gabriel Funingana, Marika Reinius, Gift Mungmeeprued, Zeyu Gao, Cathal McCague, Eric Kerfoot, Ramona Woitek, Evis Sala, Yangming Ou, James D. Brenton, Julia A. Schnabel, Mireia Crispin:
A Self-Supervised Image Registration Approach for Measuring Local Response Patterns in Metastatic Ovarian Cancer. CoRR abs/2407.17114 (2024) - 2023
- [j16]Thomas Buddenkotte
, Lorena Escudero Sanchez
Calibrating ensembles for scalable uncertainty quantification in deep learning-based medical image segmentation. Comput. Biol. Medicine 163: 107096 (2023) - [j15]Moloud Abdar
Binarized multi-gate mixture of Bayesian experts for cardiac syndrome X diagnosis: A clinician-in-the-loop scenario with a belief-uncertainty fusion paradigm. Inf. Fusion 97: 101813 (2023) - [j14]Michael Yeung
Calibrating the Dice Loss to Handle Neural Network Overconfidence for Biomedical Image Segmentation. J. Digit. Imaging 36(2): 739-752 (2023) - [j13]Sören Dittmer
Navigating the development challenges in creating complex data systems. Nat. Mac. Intell. 5(7): 681-686 (2023) - 2022
- [j12]Michael Yeung, Evis Sala, Carola-Bibiane Schönlieb, Leonardo Rundo
Unified Focal loss: Generalising Dice and cross entropy-based losses to handle class imbalanced medical image segmentation. Comput. Medical Imaging Graph. 95: 102026 (2022) - [j11]Xiang Bai, Hanchen Wang, Liya Ma, Yongchao Xu, Jiefeng Gan
Author Correction: Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence. Nat. Mach. Intell. 4(4): 413 (2022) - [c3]Michael Yeung, Leonardo Rundo
Focal Attention Networks: Optimising Attention for Biomedical Image Segmentation. ISBI 2022: 1-5 - [i11]Tolou Shadbahr, Michael Roberts, Jan Stanczuk, Julian D. Gilbey
Classification of datasets with imputed missing values: does imputation quality matter? CoRR abs/2206.08478 (2022) - [i10]Thomas Buddenkotte, Lorena Escudero Sanchez, Mireia Crispin-Ortuzar, Ramona Woitek, Cathal McCague
Calibrating Ensembles for Scalable Uncertainty Quantification in Deep Learning-based Medical Segmentation. CoRR abs/2209.09563 (2022) - 2021
- [j10]Changhee Han
MADGAN: unsupervised medical anomaly detection GAN using multiple adjacent brain MRI slice reconstruction. BMC Bioinform. 22-S(2): 31 (2021) - [j9]Michael Yeung
Focus U-Net: A novel dual attention-gated CNN for polyp segmentation during colonoscopy. Comput. Biol. Medicine 137: 104815 (2021) - [j8]Maureen van Eijnatten
3D deformable registration of longitudinal abdominopelvic CT images using unsupervised deep learning. Comput. Methods Programs Biomed. 208: 106261 (2021) - [j7]Michael Roberts
Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans. Nat. Mach. Intell. 3(3): 199-217 (2021) - [j6]Xiang Bai, Hanchen Wang, Liya Ma, Yongchao Xu, Jiefeng Gan
Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence. Nat. Mach. Intell. 3(12): 1081-1089 (2021) - [j5]Leonardo Rundo
A CUDA-powered method for the feature extraction and unsupervised analysis of medical images. J. Supercomput. 77(8): 8514-8531 (2021) - [i9]Michael Yeung, Evis Sala, Carola-Bibiane Schönlieb, Leonardo Rundo:
A Mixed Focal Loss Function for Handling Class Imbalanced Medical Image Segmentation. CoRR abs/2102.04525 (2021) - [i8]Michael Yeung, Evis Sala, Carola-Bibiane Schönlieb, Leonardo Rundo:
Advances in Artificial Intelligence to Reduce Polyp Miss Rates during Colonoscopy. CoRR abs/2105.07467 (2021) - [i7]Michael Yeung, Leonardo Rundo, Yang Nan, Evis Sala, Carola-Bibiane Schönlieb, Guang Yang:
Calibrating the Dice loss to handle neural network overconfidence for biomedical image segmentation. CoRR abs/2111.00528 (2021) - [i6]Michael Yeung, Guang Yang, Evis Sala, Carola-Bibiane Schönlieb, Leonardo Rundo:
Incorporating Boundary Uncertainty into loss functions for biomedical image segmentation. CoRR abs/2111.00533 (2021) - [i5]Michael Yeung, Leonardo Rundo, Evis Sala, Carola-Bibiane Schönlieb, Guang Yang:
Focal Attention Networks: optimising attention for biomedical image segmentation. CoRR abs/2111.00534 (2021) - [i4]Xiang Bai, Hanchen Wang, Liya Ma, Yongchao Xu, Jiefeng Gan, Ziwei Fan, Fan Yang, Ke Ma, Jiehua Yang, Song Bai, Chang Shu, Xinyu Zou, Renhao Huang, Changzheng Zhang, Xiaowu Liu, Dandan Tu, Chuou Xu, Wenqing Zhang, Xi Wang, Anguo Chen, Yu Zeng, Dehua Yang, Ming-Wei Wang, Nagaraj Holalkere, Neil J. Halin, Ihab R. Kamel, Jia Wu, Xuehua Peng, Xiang Wang, Jianbo Shao, Pattanasak Mongkolwat, Jianjun Zhang, Weiyang Liu, Michael Roberts, Zhongzhao Teng, Lucian Beer, Lorena Escudero Sanchez, Evis Sala, Daniel L. Rubin, Adrian Weller, Joan Lasenby, Chuangsheng Zheng, Jianming Wang, Zhen Li, Carola-Bibiane Schönlieb, Tian Xia:
Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence. CoRR abs/2111.09461 (2021) - 2020
- [j4]Leonardo Rundo
Tissue-specific and interpretable sub-segmentation of whole tumour burden on CT images by unsupervised fuzzy clustering. Comput. Biol. Medicine 120: 103751 (2020) - [j3]Leonardo Rundo
A Survey on Nature-Inspired Medical Image Analysis: A Step Further in Biomedical Data Integration. Fundam. Informaticae 171(1-4): 345-365 (2020) - [j2]Leonardo Rundo
Recent advances of HCI in decision-making tasks for optimized clinical workflows and precision medicine. J. Biomed. Informatics 108: 103479 (2020) - [i3]Maureen van Eijnatten
3D deformable registration of longitudinal abdominopelvic CT images using unsupervised deep learning. CoRR abs/2005.07545 (2020) - [i2]Changhee Han, Leonardo Rundo, Kohei Murao, Tomoyuki Noguchi, Yuki Shimahara, Zoltán Ádám Milacski, Saori Koshino, Evis Sala, Hideki Nakayama, Shin'ichi Satoh:
MADGAN: unsupervised Medical Anomaly Detection GAN using multiple adjacent brain MRI slice reconstruction. CoRR abs/2007.13559 (2020) - [i1]Michael Roberts
Machine learning for COVID-19 detection and prognostication using chest radiographs and CT scans: a systematic methodological review. CoRR abs/2008.06388 (2020)
2010 – 2019
- 2019
- [c2]Changhee Han, Leonardo Rundo
GAN-Based Multiple Adjacent Brain MRI Slice Reconstruction for Unsupervised Alzheimer's Disease Diagnosis. CIBB 2019: 44-54 - [c1]Leonardo Rundo
HaraliCU: GPU-Powered Haralick Feature Extraction on Medical Images Exploiting the Full Dynamics of Gray-Scale Levels. PaCT 2019: 304-318 - 2015
- [j1]Duc Fehr
Automatic classification of prostate cancer Gleason scores from multiparametric magnetic resonance images. Proc. Natl. Acad. Sci. USA 112(46): E6265-E6273 (2015)
Coauthor Index
aka: Carola Schönlieb
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last updated on 2024-11-04 20:44 CET by the dblp team
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