A method for finding high accuracy surface zones on 3D printed bone models.

The use of three-dimensional (3D) printing for surgical applications is steadily increasing. Errors in the printed models can lead to complications, especially when the model is used for surgery planning or diagnostics. In patient care, the validation of printed models should therefore be performed routinely.

A novel portable, low-cost kinect-based system for motion analysis in neurological diseases.

Many neurological diseases, such as Parkinson's disease and epilepsy, can significantly impair the motor function of the patients, often leading to a dramatic loss of their quality of life. Human motion analysis is regarded as fundamental towards an early diagnosis and enhanced follow-up in this type of diseases. In this contribution, we present NeuroKinect, a novel system designed for motion analysis in neurological diseases.

AggNet: Deep Learning From Crowds for Mitosis Detection in Breast Cancer Histology Images.

The lack of publicly available ground-truth data has been identified as the major challenge for transferring recent developments in deep learning to the biomedical imaging domain. Though crowdsourcing has enabled annotation of large scale databases for real world images, its application for biomedical purposes requires a deeper understanding and hence, more precise definition of the actual annotation task. The fact that expert tasks are being outsourced to non-expert users may lead to noisy annotations introducing disagreement between users.

NeuroKinect: A Novel Low-Cost 3Dvideo-EEG System for Epileptic Seizure Motion Quantification.

Epilepsy is a common neurological disorder which affects 0.5-1% of the world population. Its diagnosis relies both on Electroencephalogram (EEG) findings and characteristic seizure-induced body movements--called seizure semiology.