MedGIFT
Topic: SPHN IMAGINE
Swiss Personalized Health Network (SPHN) driver project Subtopics: Keywords: |
|
Publications for topic "SPHN IMAGINE"
2024
The image biomarker standardization initiative: Standardized convolutional filters for reproducible radiomics and enhanced clinical insights (2024), in: Radiology, 310:2
|
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , and ,
[DOI] |
2023
Automatic Head and Neck Tumor Segmentation and Outcome Prediction Relying on FDG-PET/CT Images: Findings from the Second Edition of the HECKTOR Challenge (2023), in: Medical Image Analysis, 90:1(102972)
|
, , , , , , , , , , and ,
[URL] |
Overview of the HECKTOR Challenge at MICCAI 2022: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT, pages 1-30, Springer, Cham, 2023 | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , and ,
[DOI] [URL] |
QuantImage v2: A Comprehensive and Integrated Physician-Centered Cloud Platform for Radiomics and Machine Learning Research (2023), in: European Radiology Experimental, 7:16
|
, , , , , , , , and ,
|
Rethinking the Role of AI with Physicians in Oncology: Revealing Perspectives from Clinical and Research Workflows, in: ACM CHI 2023, 2023 | , , , , , , and ,
[DOI] [URL] |
2022
Cleaning Radiotherapy Contours for Radiomics Studies, is it Worth it? A Head and Neck Cancer Study (2022), in: Clinical and Translational Radiation Oncology, 33(153-158)
|
, , , , , , , , , and ,
|
Comparison of MR preprocessing strategies and sequences for radiomics-based MGMT prediction, in: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries (MICCAI/BrainLes 2021), Cham, pages 367–380, Springer International Publishing, 2022 | , , , , , , , and ,
[DOI] |
Head and Neck Tumor Segmentation and Outcome Prediction, Springer International Publishing, 2022 |
[DOI] [URL] |
HEad and neCK TumOR segmentation and outcome prediction: The HECKTOR challenge, in: European Society of Radiology, 2022 | , , , , , , , and ,
|
Head and Neck Tumor Segmentation in PET/CT: The HECKTOR Challenge (2022), in: Medical Image Analysis, 77(102336)
|
, , , , , , , , , , , , , , , , , , , , , , , , , and ,
[URL] |
Multi-Organ Nucleus Segmentation Using a Locally Rotation Invariant Bispectral U-Net, in: Medical Imaging with Deep Learning, 2022 | , , , and ,
[URL] |
Overview of the HECKTOR Challenge at MICCAI 2021: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT Images, in: Head and Neck Tumor Segmentation and Outcome Prediction, pages 1-37, 2022 | , , , , , , , , , and ,
[DOI] [URL] |
QuantImage v2: A Clinician-in-the-loop Cloud Platform for Radiomics Research, in: European Society of Radiology, 2022 | , , , , , , , and ,
|
Segmentation and Classification of Head and Neck Nodal Metastases and Primary Tumors in PET/CT, in: 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), pages 4731-4735, 2022 | , , , , and ,
|
The Image Biomarker Standardisation Initiative (IBSI) On Reproducible Convolutional Radiomics, in: European Society of Radiology, 2022 | , , , , , and ,
|
2021
Assessment of the stability and discriminative power of radiomics features in liver lesions using an anthropomorphic 3D-printed CT phantom, in: Scientific session SGR-SSR, 2021 | , , , , , , , , and ,
|
Fully Automatic Head and Neck Cancer Prognosis Prediction in PET/CT, in: Multimodal Learning for Clinical Decision Support, pages 59-68, Springer LNCS, 2021 | , , , , , and ,
|
Multi-Task Deep Segmentation and Radiomics for Automatic Prognosis in Head and Neck Cancer, in: 4th Workshop on PRedictive Intelligence in MEdicine, pages 147-156, Springer LNCS, 2021 | , , , , , and ,
[URL] |
Overview of the HECKTOR Challenge at MICCAI 2020: Automatic Head and Neck Tumor Segmentation in PET/CT, pages 1-21, 2021 | , , , , , , and ,
|
QuantImage v2: an Open-Source and Web-Based Integrated Platform for Clinical Radiomics Research, in: Joint scientific session SSRMP/SGR-SSR, 2021 | , , , and ,
|
Revealing most suitable CT radiomics features for retrospective studies with heterogeneous datasets, in: European Congress of Radiology (ECR) 2021, ONLINE edition, 2021 | , , , , , , , , and ,
|
The discriminative power and stability of radiomics features with CT variations: Task-based analysis in an anthropomorphic 3D-printed CT phantom (2021), in: Investigative Radiology, 56:12(820-825)
|
, , , , , , , , and ,
|
2020
3D Solid Spherical Bispectrum CNNs for Biomedical Texture Analysis, 2020
|
, , , and ,
[URL] |
Automatic Segmentation of Head and Neck Tumors and Nodal Metastases in PET-CT scans, in: Medical Imaging with Deep Learning, Montréal, Canada, 2020 | , , , , , , , and ,
[URL] |
Local Rotation Invariance in 3D CNNs (2020), in: Medical Image Analysis, 65(101756)
|
, , , and ,
[DOI] [URL] |
Oropharynx Detection in PET-CT for Tumor Segmentation, in: Irish Machine Vision and Image Processing Conference, 2020, 2020 | , and ,
|
Standardised convolutional filtering for radiomics, 2020 | , , , , , , and ,
[URL] |
The Importance of Feature Aggregation in Radiomics: A Head and Neck Cancer Study (2020), in: Nature Scientific Reports, 10:19679
|
, , , , and ,
|