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 infrastructure and participants placed their programs in virtual machines on the cloud. The book presents the points of view of both the organizers of the VISCERAL benchmarks and the participants. The book is divided into five parts. Part I presents the cloud-based benchmarking and Evaluation-as-a-Service paradigm that the VISCERAL benchmarks used. Part II focuses on the datasets of medical images annotated with ground truth created in VISCERAL that continue to be available for research. It also covers t...
Rapid advances in image processing capabilities have been seen across many domains, fostered by the ...
Abstract. Medical visual information retrieval has been a very active research area over the past te...
Typical medical image annotation systems use manual annotation or complex proprietary software such ...
Variations in the shape and appearance of anatomical structures in medical images are often relevant...
Variations in the shape and appearance of anatomical structures in medical images are often relevant...
Systematic evaluation has had a strong impact on many data analysis domains, for example, TREC and C...
This chapter gives a brief overview of the VISCERAL Registration System that is used for all the VIS...
Many widely used digital medical image collections have been established but these are generally use...
VISCERAL (Visual Concept Extraction Challenge in Radiology) aims to organize series of benchmarks on...
The results of the VISCERAL 3D case retrieval benchmark were presented during the Multimodal Retriev...
The VISual Concept Extraction challenge in RAdioLogy (VISCERAL) project has been developed as a clou...
Health providers currently construct their differential diagnosis for a given medical case most ofte...
This is an overview paper describing the data and evaluation scheme of the VISCERAL Segmentation Cha...
To help manage the large amount of biomedical images produced, image information retrieval tools hav...
Rapid advances in image processing capabilities have been seen across many domains, fostered by the ...
Rapid advances in image processing capabilities have been seen across many domains, fostered by the ...
Abstract. Medical visual information retrieval has been a very active research area over the past te...
Typical medical image annotation systems use manual annotation or complex proprietary software such ...
Variations in the shape and appearance of anatomical structures in medical images are often relevant...
Variations in the shape and appearance of anatomical structures in medical images are often relevant...
Systematic evaluation has had a strong impact on many data analysis domains, for example, TREC and C...
This chapter gives a brief overview of the VISCERAL Registration System that is used for all the VIS...
Many widely used digital medical image collections have been established but these are generally use...
VISCERAL (Visual Concept Extraction Challenge in Radiology) aims to organize series of benchmarks on...
The results of the VISCERAL 3D case retrieval benchmark were presented during the Multimodal Retriev...
The VISual Concept Extraction challenge in RAdioLogy (VISCERAL) project has been developed as a clou...
Health providers currently construct their differential diagnosis for a given medical case most ofte...
This is an overview paper describing the data and evaluation scheme of the VISCERAL Segmentation Cha...
To help manage the large amount of biomedical images produced, image information retrieval tools hav...
Rapid advances in image processing capabilities have been seen across many domains, fostered by the ...
Rapid advances in image processing capabilities have been seen across many domains, fostered by the ...
Abstract. Medical visual information retrieval has been a very active research area over the past te...
Typical medical image annotation systems use manual annotation or complex proprietary software such ...