Institute of Informatics (II)
Topic: MedGIFT
Publications for topic "MedGIFT"
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2020
, , , , and , The Importance of Feature Aggregation in Radiomics: A Head and Neck Cancer Study (2020), in: Nature Scientific Reports, 10:19679
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2019
| , , and , A lung graph model for the classification of interstitial lung disease on CT images, in: SPIE Medical Imaging 2019: Computer-Aided Diagnosis, International Society for Optics and Photonics, pages 869-876, SPIE, 2019 |
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| , , , and , Deep learning based retrieval system for gigapixel histopathology cases and open access literature (2019), in: Pathology Informatics |
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, , , and , Exploring local rotation invariance in 3D CNNs with steerable filters, in: Medical Imaging with Deep Learning, pages 15-26, Proceedings of Machine Learning Research, 2019
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, , and , Fusing Learned Representations from Riesz and Deep CNNs for Lung Tissue Classification (2019), in: Medical Image Analysis, 56(172-183)
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| , and , Learning Cross-Protocol Radiomics and Deep Feature Standardization from CT Images of Texture Phantoms, in: SPIE Medical Imaging 2019, International Society for Optics and Photonics, pages 109-116, SPIE, 2019 |
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| , and , Neural Network Training for Cross-Protocol Radiomic Feature Standardization in Computed Tomography (2019), in: Journal of Medical Imaging, 6:3(024008) |
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, , , , , , , , , , , , and , PET-based predictive survival model after radiotherapy for head and neck cancer (2019), in: European Journal of Nuclear Medicine and Molecular Imaging, 46:3(638-649)
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| , , , , and , Radial B-Splines for Optimal Detection in Images, in: ISBI Special Session on Spline Models in Biomedical Imaging, 2019 |
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, , , , , and , Revealing Tumor Habitats from Texture Heterogeneity Analysis for Classification of Lung Cancer Malignancy and Aggressiveness (2019), in: Nature Scientific Reports, 9:1(4500)
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| , , , and , Solid Spherical Energy (SSE) CNNs for Efficient 3D Medical Image Analysis, in: Irish Machine Vision and Image Processing Conference, pages 37-44, 2019 |
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, and , Texture-Driven Parametric Snakes for Semi-Automatic Image Segmentation (2019), in: Computer Vision and Image Understanding, 188(102793)
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2018
| , , , and , Deep learning based retrieval system for gigapixel histopathology cases and open access literature (2018), in: BioArXiv |
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| , and , Distributed container-based evaluation platform for private/large datasets, in: ISPDC 2018, Geneva, Switzerland, 2018 |
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| , , and , Fast Rotational Sparse Coding (2018)(arXiv:1806.04374) |
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| , , , , , , , , and , Locoregional radiogenomic models to capture gene expression heterogeneity in glioblastoma (2018), in: biorXiv |
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| , , , and , Rotation Invariance and Directional Sensitivity: Spherical Harmonics versus Radiomics Features, in: Machine Learning in Medical Imaging (MLMI), pages 107--115, Springer International Publishing, 2018 |
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| , and , Rotation-Covariant Tissue Analysis for Interstitial Lung Diseases Using Learned Steerable Filters: Performance Evaluation and Relevance for Diagnostic Aid (2018), in: Computerized Medical Imaging and Graphics, 64(1-11) |
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| and , Rotational 3D Texture Classification Using Group Equivariant CNNs (2018), in: ArXiv |
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, , , , , , , , , and , The Use of Texture Based Radiomics CT Analysis to Predict Outcomes in Early-Stage Non-Small Cell Lung Cancer Treated with Stereotactic Ablative Radiotherapy (2018), in: The British Journal of Radiology, 92:1094(20180228)
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2017
, , , and , 3-D Solid Texture Classification Using Locally-Oriented Wavelet Transforms (2017), in: IEEE Transactions on Image Processing, 26:4(1899-1910)
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, , , , , , , , , , , , and , A PET-based nomogram for oropharyngeal cancers (2017), in: European Journal of Cancer, 75(222-230)
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| , and , Biomedical Texture Analysis: Fundamentals, Applications and Tools, Elsevier, Elsevier-MICCAI Society Book series, 2017 |
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| and , Biomedical Texture Operators and Aggregation Functions: A Methodological Review and User’s Guide, in: Biomedical Texture Analysis: Fundamentals, Applications and Tools, pages 55-94, Elsevier, 2017 |
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| , and , Combining Radiology Images and Meta-data for Multimodal Medical Case-Based Retrieval, Springer, 2017 |
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| , , , , , , and , Convolutional neural networks for an automatic classification of prostate tissue slides with high-grade Gleason score, in: SPIE Medical Imaging, pages 101400O-101400O-9, 2017 |
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| , , , , , , and , Elsevier book on Texture Analysis, chapter Analysis of Histopathology Images: From Traditional Machine Learning to Deep Learning, 2017 |
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| , and , Fundamentals of Texture Processing for Biomedical Image Analysis: A General Definition and Problem Formulation, in: Biomedical Texture Analysis: Fundamentals, Applications and Tools, pages 1-27, Elsevier, 2017 |
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, , , , , and , Metabolic Tumor Volume and Total Lesion Glycolysis in Oropharyngeal Cancer treated with definitive radiotherapy: Which threshold is the best predictor of local control ? (2017), in: Clinical Nuclear Medicine, 42:6(e281–e285)
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| , Multi-Scale and Multi-Directional Biomedical Texture Analysis: Finding the Needle in the Haystack, in: Biomedical Texture Analysis: Fundamentals, Applications and Tools, pages 29-53, Elsevier, 2017 |
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| , , , , , and , QuantImage: An Online Tool for High-Throughput 3D Radiomics Feature Extraction in PET-CT, in: Biomedical Texture Analysis: Fundamentals, Applications and Tools, pages 349-377, Elsevier, 2017 |
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| , , , and , Retrieval of Medical Cases for Diagnostic Decisions: VISCERAL Retrieval Benchmark, chapter Retrieval of Medical Cases for Diagnostic Decisions: VISCERAL Retrieval Benchmark, Springer, 2017 |
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, , , , , , , and , Signature of Survival: A 18F-FDG PET Based Whole-Liver Radiomics Analysis Predicts Survival After 90Y-TARE for Hepatocellular Carcinoma (2017), in: OncoTarget, 9:4(4549-4558)
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, , and , Steerable Wavelet Machines (SWM): Learning Moving Frames for Texture Classification (2017), in: IEEE Transactions on Image Processing, 26:4(1626-1636)
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| , , , and , Text- and content-based medical image retrievals in the VISCERAL retrieval benchmark, Springer, 2017 |
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| , and , VISCERAL book, Springer, 2017 |
| and , VISCERAL: Evaluation-as-a-Service for Medical Imaging, VISCERAL book, Springer, 2017 |
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2016
, , , , , , , and , A 3-D Riesz-Covariance Texture Model for Prediction of Nodule Recurrence in Lung CT (2016), in: IEEE Transactions on Medical Imaging, 35:12(2620-2630)
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| , and , A Demo of Multimodal Medical Retrieval, in: Workshop on Content-based Multimedia Indexing (CBMI), Bucharest, Romania, 2016 |
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| , , , , , and , A Lung Graph-Model for Pulmonary Hypertension and Pulmonary Embolism Detection on DECT images, in: MICCAI Workshop on Medical Computer Vision: Algorithms for Big Data, pages 58-68, 2016 |
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, , and , Automated Classification of Brain Tumor Type in Whole-Slide Digital Pathology Images Using Local Representative Tiles (2016), in: Medical Image Analysis, 30(60-71)
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| , , , , and , Bodily obstacles in mental imagery. Specific perspective-dependent effects of the apparent motion perception of an actors’ body parts (2016), in: 12th Symposium of the Zurich Center for Integrative Human Physiology (ZIHP) |
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| , , , , , , , , , , and , ChaLearn Joint Contest on Multimedia Challenges Beyond Visual Analysis: An overview (2016), in: ICPR 2016 |
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, , , , , , , and , Clinical Parameter Effect on the Capability to Control Myoelectric Robotic Prosthetic Hands (2016), in: Journal of Rehabilitation Research and Development, 53:3(345-358)
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| , , and , Clinical, anatomical and external factors to improve dexterous robotic hand prostheses, in: XXI Congress of the Federation of European Societies for Surgery of the Hand (FESSH), Santander, Spain, 2016 |
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, , , , , , , , , , , , , , , , , , , , , , , , , , and , Cloud–based Evaluation of Organ Segmentation and Landmark Detection Algorithms: VISCERAL Anatomy Benchmarks (2016), in: IEEE Transactions on Medical Imaging
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| , , , , , , , , , , , , , , , , , , and , Computational Fluid Dynamics as a tool to predict the air pollution dispersion in a neighbourhood – A research project to improve the quality of life in cities, in: Air pollution, Crete, Greece, 2016 |
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, , , , , , and , Creating a Large-Scale Silver Corpus from Multiple Algorithmic Segmentations, in: MICCAI medical computer vision workshop at MICCAI 2015, Munich, Germany, 2016
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, and , Deep learning with convolutional neural networks: a resource for the control of robotic prosthetic hands via electromyography (2016), in: Frontiers in Neurorobotics, 10(9)
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| , , , , and , Div150Multi: A Social Image Retrieval Result Diversification Dataset with Multi-topic Queries, in: Multimedia Systems, Klagenfurt, Austria, 2016 |
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| 1-50 | 51-100 | 101-150 | 151-200 | 201-250 | 251-300 | 301-350 | 351-400 | 401-450 | 451-500 | 501-550 | 551-590 |