Cloud-Based Benchmarking of Medical Image Analysis
This book is open access under a CC BY-NC 2.5 license. This book presents the VISCERAL project benchmarks for analysis and retrieval of 3D medical images (CT and MRI) on a large scale, which used an innovative cloud-based evaluation approach where the image data were stored centrally on a cloud infr...
I tiakina i:
Kaituhi rangatōpū: | |
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Ētahi atu kaituhi: | , , |
Hōputu: | Tāhiko īPukapuka |
Reo: | Ingarihi |
I whakaputaina: |
Cham :
Springer International Publishing : Imprint: Springer,
2017.
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Ngā marau: | |
Urunga tuihono: | http://dx.doi.org/10.1007/978-3-319-49644-3 |
Ngā Tūtohu: |
Tāpirihia he Tūtohu
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
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Rārangi ihirangi:
- VISCERAL: Evaluation-as-a-Service for Medical Imaging
- Using the Cloud as a Platform for Evaluation and Data Preparation
- Ethical and Privacy Aspects of Using Medical Image Data
- Annotating Medical Image Data
- Datasets created in VISCERAL
- Evaluation Metrics for Medical Organ Segmentation and Lesion Detection
- VISCERAL Anatomy Benchmarks for Organ Segmentation and Landmark Localisation: Tasks and Results
- Retrieval of Medical Cases for Diagnostic Decisions: VISCERAL Retrieval Benchmark
- Automatic Atlas-Free Multi-Organ Segmentation of Contrast-Enhanced CT Scans
- Multi-organ Segmentation Using Coherent Propagating Level Set Method Guided by Hierarchical Shape Priors and Local Phase Information
- Automatic Multi-organ Segmentation using Hierarchically-Registered Probabilistic Atlases
- Multi-Atlas Segmentation Using Robust Feature-Based Registration
- Combining Radiology Images and Clinical Meta-data for Multimodal Medical Case-based Retrieval
- Text and Content-based Medical Image Retrieval in the VISCERAL Retrieval Benchmark.