MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Vision

Prior to the deep learning era, shape was commonly used to describe the objects. Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly diverging from computer vision, where voxel grids, meshes, point clouds, and implicit surface models are used. This is seen from numerous shape-related publications in premier vision conferences as well as the growing popularity of ShapeNet (about 51,300 models) and Princeton ModelNet (127,915 models). For the medical domain, we present a large collection of anatomical shapes (e.g., bones, organs, vessels) and 3D models of surgical instrument, called MedShapeNet, created to facilitate the translation of data-driven vision algorithms to medical applications and to adapt SOTA vision algorithms to medical problems. As a unique feature, we directly model the majority of shapes on the imaging data of real patients. As of today, MedShapeNet includes 23 dataset with more than 100,000 shapes that are paired with annotations (ground truth). Our data is freely accessible via a web interface and a Python application programming interface (API) and can be used for discriminative, reconstructive, and variational benchmarks as well as various applications in virtual, augmented, or mixed reality, and 3D printing. Exemplary, we present use cases in the fields of classification of brain tumors, facial and skull reconstructions, multi-class anatomy completion, education, and 3D printing. In future, we will extend the data and improve the interfaces. The project pages are: https://medshapenet.ikim.nrw/ and https://github.com/Jianningli/medshapenet-feedbackComment: 16 page

A practical guide and decision-making protocol for the management of complex renal cystic masses

Objectives: To analyse the management, pathology and outcomes of complex renal cystic masses (CRCM) and to develop a decision-making tool for daily clinical care using the Bosniak classification system for CRCM. Patients and methods: A comprehensive dataset of 185 patients with 188 CRCM and a minimum follow-up of 3 years were analysed for management, pathology and outcomes. Results: We analysed 35 Bosniak II, 34 Bosniak IIF, 58 Bosniak III, and 61 Bosniak IV lesions. The overall incidence of renal cell carcinoma was 8.6%, 29.4%, 62.1%, and 78.7% for each category. Based on our surveillance strategy of Bosniak IIF masses, we recommend computed tomography (CT)/magnetic resonance imaging (MRI) every 2 years after the initial examination. We also recommend performing one MRI (as an adjunct to CT) during the early follow-up period (<4 years). The use of MRI correlation for differential diagnostic purposes has proven useful for marginal Bosniak II, IIF and III cases. Conclusions: From our data, we have created a decision-making protocol to guide urologists in planning a safe and effective diagnostic and treatment strategy for CRCM. The Bosniak classification is a useful tool for clinical decision-making. Uncertainties still remain for Bosniak IIF and III lesions. Our protocol shows that individualised decision-making is necessary in a significant proportion of CRCM

CHAMP (Camera, Handlens, and Microscope Probe)

CHAMP (Camera, Handlens And Microscope Probe)is a novel field microscope capable of color imaging with continuously variable spatial resolution from infinity imaging down to diffraction-limited microscopy (3 micron/pixel). As a robotic arm-mounted imager, CHAMP supports stereo imaging with variable baselines, can continuously image targets at an increasing magnification during an arm approach, can provide precision rangefinding estimates to targets, and can accommodate microscopic imaging of rough surfaces through a image filtering process called z-stacking. CHAMP was originally developed through the Mars Instrument Development Program (MIDP) in support of robotic field investigations, but may also find application in new areas such as robotic in-orbit servicing and maintenance operations associated with spacecraft and human operations. We overview CHAMP'S instrument performance and basic design considerations below

A Major Upgrade of the H.E.S.S. Cherenkov Cameras

The High Energy Stereoscopic System (H.E.S.S.) is an array of imaging atmospheric Cherenkov telescopes (IACTs) located in Namibia. It was built to detect Very High Energy (VHE, >100 GeV) cosmic gamma rays, and consists of four 12 m diameter Cherenkov telescopes (CT1-4), built in 2003, and a larger 28 m telescope (CT5), built in 2012. The larger mirror surface of CT5 permits to lower the energy threshold of the array down to 30 GeV. The cameras of CT1-4 are currently undergoing an extensive upgrade, with the goals of reducing their failure rate, reducing their readout dead time and improving the overall performance of the array. The entire camera electronics has been renewed from ground-up, as well as the power, ventilation and pneumatics systems, and the control and data acquisition software. Technical solutions forseen for the next-generation Cherenkov Telescope Array (CTA) observatory have been introduced, most notably the readout is based on the NECTAr analog memory chip. The camera control subsystems and the control software framework also pursue an innovative design, increasing the camera performance, robustness and flexibility. The CT1 camera has been upgraded in July 2015 and is currently taking data; CT2-4 will upgraded in Fall 2016. Together they will assure continuous operation of H.E.S.S at its full sensitivity until and possibly beyond the advent of CTA. This contribution describes the design, the testing and the in-lab and on-site performance of all components of the newly upgraded H.E.S.S. camera

The upgrade of the H.E.S.S. cameras

International audienceThe High Energy Stereoscopic System (H.E.S.S.) is an array of five imaging atmospheric Cherenkov telescopes (IACT) located in Namibia. In order to assure the continuous operation of H.E.S.S. at its full sensitivity until and possibly beyond the advent of CTA, the older cameras, installed in 2003, are currently undergoing an extensive upgrade. Its goals are reducing the system failure rate, reducing the dead time and improving the overall performance of the array. All camera components have been upgraded, except the mechanical structure and the photo-multiplier tubes (PMTs). Novel technical solutions have been introduced: the upgraded readout electronics is based on the NECTAr analog memory chip; the control of the hardware is carried out by an FPGA coupled to an embedded ARM computer; the control software was re-written from scratch and it is based on modern C++ open source libraries. These hardware and software solutions offer very good performance, robustness and flexibility. The first camera was fielded in July 2015 and has been successfully commissioned; the rest is scheduled to be upgraded in September 2016. The present contribution describes the design, the testing and the performance of the new H.E.S.S. camera and its components

Hardware and software architecture of the upgraded H.E.S.S. cameras

International audienceIn 2015/16, the photomultiplier cameras of the H.E.S.S. Cherenkov telescopes CT1-4 have undergone a major upgrade. The entire electronics has been replaced, using NECTAr chips for the front-end readout. A new ventilation system has been installed and several auxiliary components have been replaced. Besides this, the internal control and readout software was rewritten from scratch in a modern and modular way. Ethernet technology was used wherever possible to ensure both flexibility, stability and high bandwidth. An overview of the installed components will be given

Upgraded Cameras for the H.E.S.S. Imaging Atmospheric Cherenkov Telescopes

International audienceThe High Energy Stereoscopic System (H.E.S.S.) is an array of five imaging atmospheric Cherenkov telescopes, sensitive to cosmic gamma rays of energies between ~30 GeV and several tens of TeV. Four of them started operations in 2003 and their photomultiplier tube (PMT) cameras are currently undergoing a major upgrade, with the goals of improving the overall performance of the array and reducing the failure rate of the ageing systems. With the exception of the 960 PMTs, all components inside the camera have been replaced: these include the readout and trigger electronics, the power, ventilation and pneumatic systems and the control and data acquisition software. New designs and technical solutions have been introduced: the readout makes use of the NECTAr analog memory chip, which samples and stores the PMT signals and was developed for the Cherenkov Telescope Array (CTA). The control of all hardware subsystems is carried out by an FPGA coupled to an embedded ARM computer, a modular design which has proven to be very fast and reliable. The new camera software is based on modern C++ libraries such as Apache Thrift, ØMQ and Protocol buffers, offering very good performance, robustness, flexibility and ease of development. The first camera was upgraded in 2015, the other three cameras are foreseen to follow in fall 2016. We describe the design, the performance, the results of the tests and the lessons learned from the first upgraded H.E.S.S. camera.© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only