User profiles for "author:Spyridon Bakas"
 | Spyridon BakasAssociate Professor, Indiana University. - Director, Division of Computational Pathology Verified email at iu.edu Cited by 18202 |
[HTML][HTML] The future of digital health with federated learning
Data-driven machine learning (ML) has emerged as a promising approach for building
accurate and robust statistical models from medical data, which is collected in huge volumes …
accurate and robust statistical models from medical data, which is collected in huge volumes …
Advanced magnetic resonance imaging in glioblastoma: a review
G Shukla, GS Alexander, S Bakas… - Chinese clinical …, 2017 - cco.amegroups.org
Glioblastoma, the most common and most rapidly progressing primary malignant tumor of
the central nervous system, continues to portend a dismal prognosis, despite improvements …
the central nervous system, continues to portend a dismal prognosis, despite improvements …
Understanding metric-related pitfalls in image analysis validation
Validation metrics are key for tracking scientific progress and bridging the current chasm
between artificial intelligence research and its translation into practice. However, increasing …
between artificial intelligence research and its translation into practice. However, increasing …
[HTML][HTML] Advancing the cancer genome atlas glioma MRI collections with expert segmentation labels and radiomic features
Gliomas belong to a group of central nervous system tumors, and consist of various sub-
regions. Gold standard labeling of these sub-regions in radiographic imaging is essential for …
regions. Gold standard labeling of these sub-regions in radiographic imaging is essential for …
The image biomarker standardization initiative: standardized quantitative radiomics for high-throughput image-based phenotyping
Background Radiomic features may quantify characteristics present in medical imaging.
However, the lack of standardized definitions and validated reference values have …
However, the lack of standardized definitions and validated reference values have …
[HTML][HTML] The medical segmentation decathlon
International challenges have become the de facto standard for comparative assessment of
image analysis algorithms. Although segmentation is the most widely investigated medical …
image analysis algorithms. Although segmentation is the most widely investigated medical …
Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge
Gliomas are the most common primary brain malignancies, with different degrees of
aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, ie …
aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, ie …
[HTML][HTML] Federated learning in medicine: facilitating multi-institutional collaborations without sharing patient data
Several studies underscore the potential of deep learning in identifying complex patterns,
leading to diagnostic and prognostic biomarkers. Identifying sufficiently large and diverse …
leading to diagnostic and prognostic biomarkers. Identifying sufficiently large and diverse …
The rsna-asnr-miccai brats 2021 benchmark on brain tumor segmentation and radiogenomic classification
U Baid, S Ghodasara, S Mohan, M Bilello… - arXiv preprint arXiv …, 2021 - arxiv.org
The BraTS 2021 challenge celebrates its 10th anniversary and is jointly organized by the
Radiological Society of North America (RSNA), the American Society of Neuroradiology …
Radiological Society of North America (RSNA), the American Society of Neuroradiology …
[HTML][HTML] The liver tumor segmentation benchmark (lits)
In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark
(LiTS), which was organized in conjunction with the IEEE International Symposium on …
(LiTS), which was organized in conjunction with the IEEE International Symposium on …