BACKGROUND: The accurate screening of tumor genomic landscapes for somatic mutations using high-throughput sequencing involves a crucial step in precise clinical diagnosis and targeted therapy. However, the complex inherent features of cancer tissue,...
BACKGROUND: An automated method for identifying the anatomical region of an image independent of metadata labels could improve radiologist workflow (e.g., automated hanging protocols) and help facilitate the automated curation of large medical imagin...
International journal of computer assisted radiology and surgery
Apr 9, 2019
PURPOSE: Real-time surgical tool tracking is a core component of the future intelligent operating room (OR), because it is highly instrumental to analyze and understand the surgical activities. Current methods for surgical tool tracking in videos nee...
International journal of computer assisted radiology and surgery
Apr 9, 2019
PURPOSE: For many applications in the field of computer-assisted surgery, such as providing the position of a tumor, specifying the most probable tool required next by the surgeon or determining the remaining duration of surgery, methods for surgical...
Minimally invasive therapy & allied technologies : MITAT : official journal of the Society for Minimally Invasive Therapy
Apr 5, 2019
Acute patient treatment can heavily profit from AI-based assistive and decision support systems, in terms of improved patient outcome as well as increased efficiency. Yet, only very few applications have been reported because of the limited accessibi...
BACKGROUND: The Response Assessment in Neuro-Oncology (RANO) criteria and requirements for a uniform protocol have been introduced to standardise assessment of MRI scans in both clinical trials and clinical practice. However, these criteria mainly re...
Computational intelligence and neuroscience
Apr 1, 2019
Artificial Bee Colony (ABC) algorithm inspired by the complex search and foraging behaviors of real honey bees is one of the most promising implementations of the Swarm Intelligence- (SI-) based optimization algorithms. Due to its robust and phase-di...
Patient classification has widespread biomedical and clinical applications, including diagnosis, prognosis, and treatment response prediction. A clinically useful prediction algorithm should be accurate, generalizable, be able to integrate diverse da...
Deep learning refers to a set of computer models that have recently been used to make unprecedented progress in the way computers extract information from images. These algorithms have been applied to tasks in numerous medical specialties, most exten...
INTRODUCTION: The most common way of assessing surgical performance is by expert raters to view a surgical task and rate a trainee's performance. However, there is huge potential for automated skill assessment and workflow analysis using modern techn...
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