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LSN (Liver Surface Nodularity) is an image analysis software application intended to assist radiologists and other trained healthcare professionals in analyzing and reporting on the liver morphology depicted in computed tomography (CT) images for use in assessment of chronic liver disease. LSN is designed to assist the user in the evaluation and documentation of liver morphology, specifically liver surface nodularity, provided that the surface nodularity is adequately depicted on the CT images. LSN provides quantitative metrics related to liver fibrosis by automating segmentation of the liver surface within userdefined Regions of Interest (ROIs) and calculating distances and means related to the liver surface nodularity. LSN also offers reporting capabilities for documenting user-confirmed results, thereby facilitating communication with other trained healthcare professionals and assessment of changes over time. LSN is intended to provide image-related information that is interpreted by a trained professional, but it does not directly generate any diagnosis. The information provided by LSN should not be used in isolation when making patient management decisions. LSN is not intended for use with or for the diagnostic interpretation of mammography images.

LSN (Liver Surface Nodularity) is a post-processing software application which assists trained professionals in evaluating DICOM computed tomography image studies of patients with chronic liver disease. The software provides tools to enable the user to make quantitative measurements related to liver surface nodularity as depicted on CT images. The generated information consists of a LSN Score (reported in tenths of a millimeter), a quantitative measure of the surface nodularity based on a set of user-defined ROIs sampling the liver surface. LSN calculates the distance between the detected liver edge and a smoothed polynomial line (spline) on a pixel-by-pixel basis inside ROIs and reports the mean of these distances on a per-slice basis as well as an overall LSN Score for the imaging series. LSN provides the user with information the progression of chronic liver disease. LSN does not make clinical decisions and the information provided by LSN must not be used in isolation when making patient management decisions. The LSN Score may provide value by standardizing terminology used to describe surface neporting, thereby facilitating communications between radiologists and other clinicans invalient's treatment planning. In addition, standardized reporting metrics may also be helpful in assessing changes for the same patient over time. LSN functions by displaying a DICOM CT abdominal series to the user paints a broad region of interest (RO)) delineating the liver edge on a subset of image slices. Then, for the painted region on each slice, the edge is detected using multiple algorithms. For each detected edge, a spline is fit to the edge and the shortes from each edge pixel to the spline are calculated and averaged, resulting in a potential LSN value. The maximum LSN value calculated for an edge is reported as the LSN values for all slices on which ROIs have been painted are then averaged to determine the overall LSN score. The core LSN algorithms are implemented in platform-independent code, and have been integrated into both a standalone PC research application and a Mac-based viewer plugin for clinical use. Both platforms produce an equivalent LSN score; the sthe algorithm to require less re-work by the user. The clinical version also produces a report containing images of the scores for each slice, and the overall LSN score. The report is produced in both PDF and DICOM formats and is ready for upload to PACS.

StoneChecker is a standalone post-processing software application which assists trained professionals in evaluating DICOM computed tomography image studies of patients diagnosed with kidney stones. The software provides tools to enable the user to navigate images, select regions of interest, and generate information from those regions. The generated information consists of regional statistical measurements of image texture and heterogeneity, including means, standard deviation, skewness, and kurtosis. The information also includes regional physical measurements of stone size, volume, and position. StoneChecker does not make clinical decisions and the information provided by StoneChecker must not be used in isolation when making patient management decisions.

StoneChecker (SC) is a standalone software application intended to load DICOMformatted CT studies, let the trained user identify stone regions of interest, and provide computed information consisting of physical measurements and statistical measurements of stone heterogeneity from a single source making it easier for the user to determine the best treatment option. SC is an optional tool used during the treatment planning of a patient diagnosed with kidney stones. StoneChecker provides the user tools to select and evaluate various physical characteristics of a kidney stone displayed on a non-contrast enhanced Kidneys, Ureters, and Bladder (KUB) CT scan slice. The measurement and calculated values are displayed on the PC screen for the user and the user has an option to generate a report. The calculated output includes stone volume, mean Hounsfield Unit (HU) density, skin to stone distance, and texture values (mean, mean of positive pixels, standard deviation, skewness, kurtosis, and entropy). This data can be used by the physician as an aid to decision making and are intended to be an adjunct to other clinical data such as medical history, physical examination, and urine analysis. Thus, additional analysis of all kidney stones is required. StoneChecker software is designed exclusively for use in assessing kidney stones. StoneChecker is designed to provide easy-to-acquire useful data for helping clinicians make the best decisions for their patients. StoneChecker includes the following features: - . Processes standard DICOM image sets, - . Novel proven statistical algorithms, - Time-saving kidney stone regions of interest (ROI) and measurement tools, . - . Rapid calculation results, and - Saves results in standard Excel spreadsheets. .

IB Clinic v1.0 (Clinic) is a post-processing software toolkit designed to be integrated into existing medical image visualization applications running on standard computer hardware. Clinic accepts relevant DICOM image sets, such as dynamic perfusion and diffusion image sets. Clinic generates various perfusion- and diffusion-related parameters, standardized image sets, and image intensity differences. The results are saved to a DICOM image file and may be further visualized on an imaging workstation. Clinic is designed to aid trained physicians in advanced image assessment, treatment consideration, and monitoring of therapeutic response. The information provided by Clinic should not be used in isolation when making patient management decisions. Dynamic Perfusion Analysis - Generates parametric perfusion maps used for visualization of temporal variations in dynamic datasets, showing changes in image intensity over time. These maps may aid in the assessment of the extent and type of perfusion, blood volume and vascular permeability changes. Dynamic Diffusion Analysis - Generates apparent diffusion coefficient maps used for the visualization of apparent water movement in soft tissue throughout the body on both voxel-by-voxel and sub-voxel bases. These images may aid in the assessment of the extent of diffusion in tissue. Image Comparison - Generates co-registered image sets. Generates standardized image sets calibrated to an arbitrary scale to facilitate comparisons between independent image sets. Generates voxel-by-voxel maps of the image intensity differences between image sets acquired at different times. Facilitates selection and DICOM export of user-selected regions of interest (ROIs) These processes may enable easier identification of image intensity differences between images and easier selection and processing of ROIs.

Clinic is a platform independent image processing library which consists of a set of code modules which run on standard computer hardware that computes a variety of numerical analyses, image parameter maps, and other image manipulations based on DICOM images captured via MR and CT modalities. These actions include: - Retrieval of MR and CT DICOM image studies from PACS and/or OS-. based file storage. - Computation of parameter maps for: . - DSC perfusion (based on MR and CT studies) O - o ADC diffusion (based on MR studies) - Image manipulations (of MR and CT studies): . - Registration of images generated at different time points o - Standardized scaling of image intensities O - o Comparison of registered and/or standardized images - Region of Interest (ROI) selection o - Generation of ROI datasets in DICOM formats O - Output of the above maps in DICOM format for export to PACS and/or OS . file storage - . Generation of reports summarizing the computations performed The IB Clinic code library can be used within standalone FDA cleared applications or can be "plugged in" and launched from within other FDA cleared applications such as Aycan's OsiriX PRO workstation. They are intended for distribution both in combination and in modular form, with functional subsets geared toward specific types of image analysis and marketed with corresponding names, including IB Neuro, IB Diffusion, and IB Delta Suite.

IB Neuro™ software allows the post-processing and display of dynamically acquired MR datasets to evaluate image intensity variations over time. IB Neuro™ v1.0 plug-in accepts data from existing MRI systems, performs quality control checks and generates parametric perfusion maps such as Relative Cerebral Blood Volume (rCBV), Cerebral Blood Flow (CBF), Mean Transit Time (MTT) and Time to Peak (TTP) and sends the maps to a PACS for subsequent viewing. These images when interpreted by a trained physician may yield information useful in clinical applications. Our advanced technology is designed to be compliant with healthcare standards such as DICOM and is easily and rapidly integrated into existing medical image visualization applications.

IB Neuro "" OsiriX Plugin is software designed to analvze dynamically acquired datasets. Using well-established algorithms, parametric perfusion maps can be generated such as Relative Cerebral Blood Volume (rCBV), Cerebral Blood Flow (CBF), Mean Transit Time (MTT) and Time to Peak (TTP). The strength of our software is its ability to extend the productivity of any existing viewer, CAD workstation or PACS via a platform-independent base library that allows for quick and seamless integration into existing server and workstation applications. It also includes other critical features such as: - Enables rapid creation of a complete array of critical perfusion parameter o maps of rCBV, CBF, MTT, TTP - o Automated correction of contrast agent leakage for rCBV maps - o Automated brain mask generation - Ability to normalize parameters to normal appearing white matter (NAWM) o - o Automated report generation - View dynamic signal time course on a per-voxel basis o - Interactive Arterial Input Function (AIF) selection o - o Automatic export of perfusion parameter maps to DICOM images within the same study