Roadmap on optical security

Postprint (author's final draft

Neuroconductor: an R platform for medical imaging analysis

Neuroconductor (https://neuroconductor.org) is an open-source platform for rapid testing and dissemination of reproducible computational imaging software. The goals of the project are to: (i) provide a centralized repository of R software dedicated to image analysis, (ii) disseminate software updates quickly, (iii) train a large, diverse community of scientists using detailed tutorials and short courses, (iv) increase software quality via automatic and manual quality controls, and (v) promote reproducibility of image data analysis. Based on the programming language R (https://www.r-project.org/), Neuroconductor starts with 51 inter-operable packages that cover multiple areas of imaging including visualization, data processing and storage, and statistical inference. Neuroconductor accepts new R package submissions, which are subject to a formal review and continuous automated testing. We provide a description of the purpose of Neuroconductor and the user and developer experience

A Review of Prosthetic Interface Stress Investigations

Over the last decade, numerous experimental and numerical analyses have been conducted to investigate the stress distribution between the residual limb and prosthetic socket of persons with lower limb amputation. The objectives of these analyses have been to improve our understanding of the residual limb/prosthetic socket system, to evaluate the influence of prosthetic design parameters and alignment variations on the interface stress distribution, and to evaluate prosthetic fit. The purpose of this paper is to summarize these experimental investigations and identify associated limitations. In addition, this paper presents an overview of various computer models used to investigate the residual limb interface, and discusses the differences and potential ramifications of the various modeling formulations. Finally, the potential and future applications of these experimental and numerical analyses in prosthetic design are presented

Correction of megavoltage cone-beam CT images of the pelvic region based on phantom measurements for dose calculation purposes.

Megavoltage cone-beam CT (MVCBCT) is an imaging technology that provides a 3D representation of the patient in treatment position. Because it is a form of x-ray tomography, MVCBCT images give information about the attenuation coefficients of the imaged tissues, and thus could be used for dose calculation. However, the cupping and missing data artifacts seen on MVCBCT images can cause inaccuracies in dose calculations. To eliminate these inaccuracies, a correction method specific to pelvis imaging and based on phantom measurements has been devised. Pelvis-shaped water phantoms of three different sizes were designed and imaged with MVCBCT. Three sets of correction factors were created from the artifacts observed in these MVCBCT images by dividing the measured CT number by the predefined CT number for water. Linear interpolation is performed between the sets of correction factors to take into account the varying size of different patients. To compensate for the missing anatomy due to the limited field of view of the MVCBCT system, the MVCBCT image is complemented with the kilovoltage CT (kVCT) image acquired for treatment planning.When the correction method is applied to an anthropomorphic pelvis phantom, the standard deviation between dose calculations performed with kVCT and MVCBCT images is 0.6%, with 98% of the dose points agreeing within +/- 3%.With uncorrected MVCBCT images this percentage falls to 75%. An example of dose calculation performed with a corrected clinicalMVCBCT image of a prostate cancer patient shows that changes in anatomy of normal tissues result in variation of the dose distribution received by these tissues.This correction method enablesMVCBCT images to be used for the verification of the daily dose distribution for patients treated in the pelvis region