AIMC Topic: Workflow

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Precision and accuracy of robot-assisted technology with simplified express femoral workflow in measuring leg length and offset in total hip arthroplasty.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Semi-active robot-assisted total hip arthroplasty (THA) has two options to measure the leg length discrepancy (LLD) and combined offset (CO), the 'enhanced' femoral workflow and the so-called 'express' simplified workflow. The purpose of ...

Integration of artificial intelligence into clinical patient management: focus on cardiac imaging.

Revista espanola de cardiologia (English ed.)
Cardiac imaging is a crucial component in the management of patients with heart disease, and as such it influences multiple, inter-related parts of the clinical workflow: physician-patient contact, image acquisition, image pre- and postprocessing, st...

Rapid whole-heart CMR with single volume super-resolution.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Three-dimensional, whole heart, balanced steady state free precession (WH-bSSFP) sequences provide delineation of intra-cardiac and vascular anatomy. However, they have long acquisition times. Here, we propose significant speed-ups using ...

Computational Cytology: Lessons Learned from Pap Test Computer-Assisted Screening.

Acta cytologica
BACKGROUND: In the face of rapid technological advances in computational cytology including artificial intelligence (AI), optimization of its application to clinical practice would benefit from reflection on the lessons learned from the decades-long ...

A deep learning method for real-time intraoperative US image segmentation in prostate brachytherapy.

International journal of computer assisted radiology and surgery
PURPOSE: This paper addresses the detection of the clinical target volume (CTV) in transrectal ultrasound (TRUS) image-guided intraoperative for permanent prostate brachytherapy. Developing a robust and automatic method to detect the CTV on intraoper...

Radiomics in radiation oncology-basics, methods, and limitations.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
Over the past years, the quantity and complexity of imaging data available for the clinical management of patients with solid tumors has increased substantially. Without the support of methods from the field of artificial intelligence (AI) and machin...

A machine learning workflow for raw food spectroscopic classification in a future industry.

Scientific reports
Over the years, technology has changed the way we produce and have access to our food through the development of applications, robotics, data analysis, and processing techniques. The implementation of these approaches by the food industry ensure qual...

The Age of Data-Driven Proteomics: How Machine Learning Enables Novel Workflows.

Proteomics
A lot of energy in the field of proteomics is dedicated to the application of challenging experimental workflows, which include metaproteomics, proteogenomics, data independent acquisition (DIA), non-specific proteolysis, immunopeptidomics, and open ...

Automatic segmentation of pelvic organs-at-risk using a fusion network model based on limited training samples.

Acta oncologica (Stockholm, Sweden)
Efficient and accurate methods are needed to automatically segmenting organs-at-risk (OAR) to accelerate the radiotherapy workflow and decrease the treatment wait time. We developed and evaluated the use of a fused model Dense V-Network for its abil...