Real-time Image Processing Software Research Articles

MARFit: An Integrated Software for Real-Time MR Guided Focused Ultrasound Neuromodulation System

MR guided focused ultrasound (MRgFUS) therapy has been a promising treatment modality for many neurological disorders. However, the lack of real-time image processing software platform sets barriers for relevant pre-clinical researches. This work intends to develop an integrated software for MRgFUS therapy. The software contains three functional modules: a communication module, an image post-processing module, and a visualization module. The communication module provides a data interface with an open-source MR image reconstruction platform (Gadgetron) to receive the reconstructed MR images in real-time. The post-processing module contains the algorithms of image coordinate registration, focus localization by MR acoustic radiation force imaging (MR-ARFI), temperature and thermal dose calculations, motion correction, and temperature feedback control. The visualization module displays monitoring information and provides a user-machine interface. The software was tested to be compatible with systems from two different vendors and validated in multiple scenarios for MRgFUS. The software was tested in many ex vivo and in vivo experiments to validate its functions. The in vivo transcranial focus localization experiments were carried out for targeting the focused ultrasound in neuromodulation.

Pairing Microwell Arrays with an Affordable, Semiautomated Single-Cell Aspirator for the Interrogation of Circulating Tumor Cell Heterogeneity.

Comprehensive analysis of tumor heterogeneity requires robust methods for the isolation and analysis of single cells from patient samples. An ideal approach would be fully compatible with downstream analytic methods, such as advanced genomic testing. These endpoints necessitate the use of live cells at high purity. A multitude of microfluidic circulating tumor cell (CTC) enrichment technologies exist, but many of those perform bulk sample enrichment and are not, on their own, capable of single-cell interrogation. To address this, we developed an affordable semiautomated single-cell aspirator (SASCA) to further enrich rare-cell populations from a specialized microwell array, per their phenotypic markers. Immobilization of cells within microwells, integrated with a real-time image processing software, facilitates the detection and precise isolation of targeted cells that have been optimally seeded into the microwells. Here, we demonstrate the platform capabilities through the aspiration of target cells from an impure background population, where we obtain purity levels of 90%-100% and demonstrate the enrichment of the target population with high-quality RNA extraction. A range of low cell numbers were aspirated using SASCA before undergoing whole transcriptome and genome analysis, exhibiting the ability to obtain endpoints from low-template inputs. Lastly, CTCs from patients with castration-resistant prostate cancer were isolated with this platform and the utility of this method was confirmed for rare-cell isolation. SASCA satisfies a need for an affordable option to isolate single cells or highly purified subpopulations of cells to probe complex mechanisms driving disease progression and resistance in patients with cancer.

Design and implementation of MIMO radar real‐time imaging system based on multicore DSP

Multiple-input multiple-output (MIMO) imaging radar is a new kind of new imaging radar in recent years. It can achieve faster data acquisition speed than the traditional ground-based SAR due to the ability to get a large number of multi-channel data in a short period of time. However, traditional single-core digital signal processors (DSPs) have limited space and ability to deal with such large amount of data. To solve this problem, a real-time image processing software architecture for MIMO imaging radar algorithm is designed and carried out based on TMS320C6678 DSP of Texas Instruments (TI), which is the highest-performance fixed/floating-point DSP based on TI's KeyStone multicore architecture. The efficient imaging algorithms mapping from Matlab to DSP is realised, with efficient task allocation, resource reuse of echo data, and processing variable, and using the method of multicore parallel processing.

Intraoperative combined color and fluorescent images–based sentinel node mapping in the porcine lung: Comparison of indocyanine green with or without albumin premixing

We developed a multimodal optical imaging system for intraoperative visualization of sentinel lymph nodes (SLNs). This study is to validate our system by showing SLNs in the lung through combined optical color and fluorescent image with indocyanine green (ICG) and ICG with human serum albumin (HSA). Identical ICG concentrations of ICG only or ICG:HSA was injected into the rat footpad and porcine lung. Absolute amounts of the fluorescents were scaled on the basis of animal weights. The entire procedures were recorded using color and near-infrared (NIR) charge-coupled device (CCD) cameras simultaneously, and the 2 images were merged by real-time image processing software. All fluorescence intensity signals to background ratio (SBR) and retention rates at SLN for both fluorescents were estimated and compared. This newly developed intraoperative color and fluorescence optical imaging system successfully visualized the SLNs in animal experiments. The SLNs were identified 100% for both rat and pig under invivo conditions. Real-time image processing software overcame the low signal of NIR fluorescence images. ICG and ICG:HSA provided no significantly different SBR in the SLN images for both rat thigh and pig lung. The intraoperative optical imaging system enabled real-time image-guided surgery during SLN mapping in lung in an animal model. The ICG retention rate was similar to ICG:HSA. ICG alone can be useful for SLN imaging during lung cancer surgery.

Mosaicing of Confocal Microscopic Video Sequences: Larger Field of View and Still Higher Resolution!

Background and Aims: The development of Cellvizio-GI (Mauna Kea Technologies, Paris, France), a “through the scope” confocal fluorescence microscope, makes it possible to obtain microscopic in vivo dynamic sequences during endoscopy procedures. Recent improvements allow the stitching of successive video frames to reconstruct images with a larger field of view and higher resolution. Material and Methods: Cellvizio-GI is the result of technological breakthroughs in different fields and is composed of 3 main elements: a Laser Scanning Unit (LSU), Confocal Miniprobes, a real-time image processing software.

Real-time multispectral imaging system for online poultry fecal inspection using unified modeling language

A prototype real-time multispectral imaging system for fecal and ingesta contaminant detection on broiler carcasses has been developed. The prototype system includes a common aperture camera with three optical trim filters (517, 565 and 802-nm wavelength), which were selected by visible/NIR spectroscopy and validated by a hyperspectral imaging system with decision tree algorithm. The on-line testing results showed that the multispectral imaging technique can be used effectively for detecting feces (from duodenum, ceca, and colon) and ingesta on the surface of poultry carcasses with a processing speed of 140 birds per minute. This paper demonstrated both multispectral imaging hardware and real-time image processing software. For the software development, the Unified Modeling Language (UML) design approach was used for on-line application. The UML models included class, object, activity, sequence, and collaboration diagram. User interface model included 17 inputs and 6 outputs. A window-based real-time image processing software composed of 11 components, which represented class, architecture, and activity. Both hardware and software for a real-time fecal detection were tested at the pilot-scale poultry processing plant. The run-time of the software including online calibration was fast enough to inspect carcasses on-line with an industry requirement. Based on the preliminary test at the pilot-scale processing line, the system was able to acquire poultry images in real-time. According to the test results, the imaging system is reliable for the harsh environments and UML-based image processing software is flexible and easy to be updated when additional parameters are needed for in-plant trials.

Microcomputer system for ion microscopy digital imaging and processing.

Analytical ion microscopy is a powerful tool for biological tissue analysis as it allows direct chemical distribution imaging, even at low element concentrations. A microcomputer based digital imaging system achieving acquisition at low light level is presented. It includes a high sensitivity video camera connected to a specialized image processor subsystem. Acquired images consist of 512 x 512 pixels with 8 bits accuracy. Real-time image processing software has been implemented so that image processing may be performed on-line. Image processing software allows off-line image manipulation and correlation for biological interpretation of elemental mapping images. System capabilities are illustrated by a study of stable and radio iodine mapping in rat thyroid tissue.