Since during clinical routine, only a small portion of the increasing amounts of medical imaging data are accessible, this project aims to provide the necessary data for clinical image assessment in short time, and to conduct competitions for identifying successful computational strategies.Während der klinischen Routine kann nur ein kleiner Teil der steigenden Schnittbildmenge erfasst werden. Ziel des Projektes ist es, die nötigen Daten für die Forschung bereitzustellen, um hieran computerbasierte Identifikationsverfahren zu testen. Projektaufbau und Ablauf der Evaluationskampagnen, verwendete Datensätze, sowie Ergebnisse der Kampagnenteilnehmer werden vorgestellt
Learning Objectives 1. To become familiar with the principles and history of image computing (autom...
Aims of study: 1) Describe the importance of human visual system on lesion detection in medical ima...
Multimedia lives with images; medical images are born from digital imaging. A physician's multimedia...
Since during clinical routine, only a small portion of increasing amounts of medical imaging data ar...
The VISual Concept Extraction challenge in RAdioLogy (VISCERAL) project has been developed as a clou...
VISCERAL (Visual Concept Extraction Challenge in Radiology) aims to organize series of benchmarks on...
Visual computing addresses various aspects of the processing of image data. These aspects include th...
The need for quantitative image analysis in radiology is universal: computer-aided detection, segmen...
In the past decades the number of medical images inspected daily in health centers, as well as the c...
The maturity of current 3D rendering software in combination with recent developments in computer vi...
Systematic evaluation has had a strong impact on many data analysis domains, for example, TREC and C...
This paper presents Visual Heuristics, a consultation system for diagnosis based on thorax radiograp...
Visual abstract for Abdominal Radiology: what it is, why we need it and how to make i
RemarkOn this page, you can access data that has been used in several scientific studies. In order t...
As part of their daily workload, clinicians examine patient cases in the process of formulating a di...
Learning Objectives 1. To become familiar with the principles and history of image computing (autom...
Aims of study: 1) Describe the importance of human visual system on lesion detection in medical ima...
Multimedia lives with images; medical images are born from digital imaging. A physician's multimedia...
Since during clinical routine, only a small portion of increasing amounts of medical imaging data ar...
The VISual Concept Extraction challenge in RAdioLogy (VISCERAL) project has been developed as a clou...
VISCERAL (Visual Concept Extraction Challenge in Radiology) aims to organize series of benchmarks on...
Visual computing addresses various aspects of the processing of image data. These aspects include th...
The need for quantitative image analysis in radiology is universal: computer-aided detection, segmen...
In the past decades the number of medical images inspected daily in health centers, as well as the c...
The maturity of current 3D rendering software in combination with recent developments in computer vi...
Systematic evaluation has had a strong impact on many data analysis domains, for example, TREC and C...
This paper presents Visual Heuristics, a consultation system for diagnosis based on thorax radiograp...
Visual abstract for Abdominal Radiology: what it is, why we need it and how to make i
RemarkOn this page, you can access data that has been used in several scientific studies. In order t...
As part of their daily workload, clinicians examine patient cases in the process of formulating a di...
Learning Objectives 1. To become familiar with the principles and history of image computing (autom...
Aims of study: 1) Describe the importance of human visual system on lesion detection in medical ima...
Multimedia lives with images; medical images are born from digital imaging. A physician's multimedia...