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Calibration

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RMDL: Recalibrated multi-instance deep learning for whole slide gastric image classification.

Medical image analysis
The whole slide histopathology images (WSIs) play a critical role in gastric cancer diagnosis. However, due to the large scale of WSIs and various sizes of the abnormal area, how to select informative regions and analyze them are quite challenging du...

Predicting gamma passing rates for portal dosimetry-based IMRT QA using machine learning.

Medical physics
PURPOSE: Intensity-modulated radiation therapy (IMRT) quality assurance (QA) measurements are routinely performed prior to treatment delivery to verify dose calculation and delivery accuracy. In this work, we applied a machine learning-based approach...

Data-driven self-calibration and reconstruction for non-cartesian wave-encoded single-shot fast spin echo using deep learning.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Current self-calibration and reconstruction methods for wave-encoded single-shot fast spin echo imaging (SSFSE) requires long computational time, especially when high accuracy is needed.

A radiomics approach based on support vector machine using MR images for preoperative lymph node status evaluation in intrahepatic cholangiocarcinoma.

Theranostics
: Accurate lymph node (LN) status evaluation for intrahepatic cholangiocarcinoma (ICC) patients is essential for surgical planning. This study aimed to develop and validate a prediction model for preoperative LN status evaluation in ICC patients. : A...

Effective locomotion at multiple stride frequencies using proprioceptive feedback on a legged microrobot.

Bioinspiration & biomimetics
Limitations in actuation, sensing, and computation have forced small legged robots to rely on carefully tuned, mechanically mediated leg trajectories for effective locomotion. Recent advances in manufacturing, however, have enabled in such robots the...

SmartPulse, a machine learning approach for calibration-free dynamic RF shimming: Preliminary study in a clinical environment.

Magnetic resonance in medicine
PURPOSE: A calibration-free pulse design method is introduced to alleviate artifacts in clinical routine with parallel transmission at high field, dealing with significant inter-subject variability, found for instance in the abdomen.

Weighted Transfer Learning for Improving Motor Imagery-Based Brain-Computer Interface.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
One of the major limitations of motor imagery (MI)-based brain-computer interface (BCI) is its long calibration time. Due to between sessions/subjects variations in the properties of brain signals, typically, a large amount of training data needs to ...

Spatio-temporal deep learning models for tip force estimation during needle insertion.

International journal of computer assisted radiology and surgery
PURPOSE: Precise placement of needles is a challenge in a number of clinical applications such as brachytherapy or biopsy. Forces acting at the needle cause tissue deformation and needle deflection which in turn may lead to misplacement or injury. He...

A force-measuring and behaviour-recording system consisting of 24 individual 3D force plates for the study of single limb forces in climbing animals on a quasi-cylindrical tower.

Bioinspiration & biomimetics
This study describes the design of a new force measuring array with a quasi-cylindrical surface for measuring the 3D ground reaction forces of animals climbing on a surface with high curvature. This force-measuring array was assembled from 24 individ...

Surgical skill levels: Classification and analysis using deep neural network model and motion signals.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Currently, the assessment of surgical skills relies primarily on the observations of expert surgeons. This may be time-consuming, non-scalable, inconsistent and subjective. Therefore, an automated system that can objectivel...