AIMC Topic: Calibration

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Convolutional neural network based proton stopping-power-ratio estimation with dual-energy CT: a feasibility study.

Physics in medicine and biology
Dual-energy computed tomography (DECT) has shown a great potential for lowering range uncertainties, which is necessary for truly leveraging the Bragg peak in proton therapy. However, analytical stopping-power-ratio (SPR) estimation methods have limi...

Layer Embedding Analysis in Convolutional Neural Networks for Improved Probability Calibration and Classification.

IEEE transactions on medical imaging
In this project, our goal is to develop a method for interpreting how a neural network makes layer-by-layer embedded decisions when trained for a classification task, and also to use this insight for improving the model performance. To do this, we fi...

Predicting population health with machine learning: a scoping review.

BMJ open
OBJECTIVE: To determine how machine learning has been applied to prediction applications in population health contexts. Specifically, to describe which outcomes have been studied, the data sources most widely used and whether reporting of machine lea...

A comparison of 4 different machine learning algorithms to predict lactoferrin content in bovine milk from mid-infrared spectra.

Journal of dairy science
Lactoferrin (LF) is a glycoprotein naturally present in milk. Its content varies throughout lactation, but also with mastitis; therefore it is a potential additional indicator of udder health beyond somatic cell count. Condequently, there is an inter...

Kinematic Calibration of a Parallel 2-UPS/RRR Ankle Rehabilitation Robot.

Journal of healthcare engineering
In order to better perform rehabilitation training on the ankle joint complex in the direction of dorsiflexion/plantarflexion and inversion/eversion, especially when performing the isokinetic muscle strength exercise, we need to calibrate the kinemat...

Improving depth-of-interaction resolution in pixellated PET detectors using neural networks.

Physics in medicine and biology
Parallax error is a common issue in high-resolution preclinical positron emission tomography (PET) scanners as well as in clinical scanners that have a long axial field of view (FOV), which increases estimation uncertainty of the annihilation positio...

Application of Artificial Neural Networks for Accurate Determination of the Complex Permittivity of Biological Tissue.

Sensors (Basel, Switzerland)
Medical devices making use of radio frequency (RF) and microwave (MW) fields have been studied as alternatives to existing diagnostic and therapeutic modalities since they offer several advantages. However, the lack of accurate knowledge of the compl...

Comparison of CBCT-based dose calculation methods in head and neck cancer radiotherapy: from Hounsfield unit to density calibration curve to deep learning.

Medical physics
PURPOSE: Anatomical variations occur during head and neck (H&N) radiotherapy treatment. kV cone-beam computed tomography (CBCT) images can be used for daily dose monitoring to assess dose variations owing to anatomic changes. Deep learning methods (D...

Automatic robot-world calibration in an optical-navigated surgical robot system and its application for oral implant placement.

International journal of computer assisted radiology and surgery
PURPOSE: Robot-world calibration, used to precisely determine the spatial relation between optical tracker and robot, is regarded as an essential step for optical-navigated surgical robot system to improve the surgical accuracy. However, these method...

Needle tip force estimation by deep learning from raw spectral OCT data.

International journal of computer assisted radiology and surgery
PURPOSE: Needle placement is a challenging problem for applications such as biopsy or brachytherapy. Tip force sensing can provide valuable feedback for needle navigation inside the tissue. For this purpose, fiber-optical sensors can be directly inte...