Feature description with SIFT, SURF, BRIEF, BRISK, or FREAK? A general question answered for bone age assessment.

Solving problems in medical image processing is either generic (being applicable to many problems) or specific (optimized for a certain task). For example, bone age assessment (BAA) on hand radiographs is a frequent but cumbersome task for radiologists. For this problem, many specific solutions have been proposed.

A Survey of DICOM Viewer Software to Integrate Clinical Research and Medical Imaging.

The digital imaging and communications in medicine (DICOM) protocol is the leading standard for image data management in healthcare. Imaging biomarkers and image-based surrogate endpoints in clinical trials and medical registries require DICOM viewer software with advanced functionality for visualization and interfaces for integration. In this paper, a comprehensive evaluation of 28 DICOM viewers is performed.

Digital Imaging and Electronic Data Capture in Multi-Center Clinical Trials.

While medical image data is managed in picture archiving and communication systems (PACS) via the digital imaging and communications in medicine (DICOM) protocol, electronic data capture systems (EDCS) in clinical trials lack PACS interfacing. This complicates the trial workflow and increases errors, time, and costs. In this work, four system architectures of image integration for multi-center trials are analyzed with respect to data, function, visual, and context integration levels.

DICOM for Clinical Research: PACS-Integrated Electronic Data Capture in Multi-Center Trials.

Providing surrogate endpoints in clinical trials, medical imaging has become increasingly important in human-centered research. Nowadays, electronic data capture systems (EDCS) are used but binary image data is integrated insufficiently. There exists no structured way, neither to manage digital imaging and communications in medicine (DICOM) data in EDCS nor to interconnect EDCS with picture archiving and communication systems (PACS).

Integrated image data and medical record management for rare disease registries. A general framework and its instantiation to theGerman Calciphylaxis Registry.

Especially for investigator-initiated research at universities and academic institutions, Internet-based rare disease registries (RDR) are required that integrate electronic data capture (EDC) with automatic image analysis or manual image annotation. We propose a modular framework merging alpha-numerical and binary data capture. In concordance with the Office of Rare Diseases Research recommendations, a requirement analysis was performed based on several RDR databases currently hosted at Uniklinik RWTH Aachen, Germany.

Simplifying electronic data capture in clinical trials: workflow embedded image and biosignal file integration and analysis via web services.

To improve data quality and save cost, clinical trials are nowadays performed using electronic data capture systems (EDCS) providing electronic case report forms (eCRF) instead of paper-based CRFs. However, such EDCS are insufficiently integrated into the medical workflow and lack in interfacing with other study-related systems. In addition, most EDCS are unable to handle image and biosignal data, although electrocardiography (EGC, as example for one-dimensional (1D) data), ultrasound (2D data), or magnetic resonance imaging (3D data) have been established as surrogate endpoints in clinical trials.