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JLK-SDH is a notification-only, parallel workflow tool that is intended to assist trained radiologists to identify and communicate images of specific patients to a specialist, independent of the standard of care workflow. JLK-SDH uses an artificial intelligence algorithm to analyze images for findings suggestive of a prespecified clinical condition and to notify an appropriate user of these findings in parallel to standard of care image interpretation. Identification of suspected findings is not for diagnostic use beyond notification. Specifically, the device analyzes non-contrast CT images of the head for subdural hemorrhage (SDH) and sends notifications to a clinician that a suspected SDH has been identified and recommends a review of those images. Images can be previewed and compressed through PACS and mobile applications. Notified clinicians are responsible for viewing non-compressed images on a diagnostic viewer and engaging in appropriate patient evaluation and relevant discussion with a treating physician before making care-related decisions or requests. JLK-SDH is limited to the analysis of imaging data and should not be used in lieu of full patient evaluation or relied upon to make or confirm the diagnosis.

JLK-SDH is a radiological computer-assisted triage and notification (CADt) software package compliant with the DICOM standard. The device functions as a Non-Contrast Computed Tomography (NCCT) processing module, providing triage and notification for suspected hemispheric subdural hemorrhage (SDH). It serves as a notification-only, parallel workflow tool for hospital networks and trained clinicians. The device helps to identify and communicate specific patient images to trained radiologists, independent of the standard of care workflow. Utilizing an artificial intelligence algorithm, the system automatically receives and analyzes NCCT studies for image features indicating the presence of SDH and sends a notification to alert a radiologist of the case. This algorithm, hosted on JLK servers, is designed to analyze non-contrast CT images of the head acquired on CT scanners and forwarded to JLK servers. The mobile software module that enables user to receive and toggle notifications for suspected subdural hemorrhages identified by the JLK-SDH Image Analysis Algorithm. Users can view a patient list, and nondiagnostic CT scans through the mobile application. Image viewing through the mobile application interface is for non-diagnostic purposes only.

JLK-AILink is a software that receives digital images and data from various sources (i.e., CT scanners, MR scanners, ultrasound systems, computed & direct radiographic devices, secondary capture devices, scanners, imaging gateways, or other imaging sources). Images and analyzed data with optional modules can be stored, communicated, processed, and displayed within the system and or across computer networks at distributed locations. Typical users of this system are trained professionals including but not limited to physicians and medical technicians. The device is not intended for mammography.

JLK-AILink is a software designed to streamline the management, visualization, and communication of medical imaging data within clinical workflows. It facilitates bidirection with hospital PACS systems or imaging equipment such as MR, CT, or X-ray scanners, enabling the communication of DICOM images. This functionality ensures seamless integration with existing hospital IT infrastructure while adhering to DICOM communication standards. The software includes a DICOM viewer that offers tools for image manipulation and annotation, such as zoom, magnify, contrast adjustment, cobb angle measurement, and annotation tools, making it an efficient and userfriendly interface for medical professionals. The modular architecture allows healthcare institutions to integrate optional analysis solutions with DICOM communication to expand its image analysis capabilities as needed. JLK-AlLink also supports mobile access, enabling clinicians to view images, interact with annotations, and receive critical alerts remotely. With a focus on interoperability, the software ensures compatibility not only with PACS systems but also with containerized environments, allowing for secure and data management. This combination of DICOM functionalities, modular integration, and mobile accessibility makes ILK-AILink a clinical tool for enhancing clinical workflows and improving the efficiency of medical imaging data usage in diverse healthcare settings.

JLK-ICH is a radiological computer-aided triage and notification software indicated for use in the analysis of non-contrast CT images. JLK-ICH is a notification-only, parallel workflow tool that is intended to assist hospital networks and trained clinicians to identify and communicate images of specific patients to specialists, independent of the standard of care workflow. JLK-ICH uses an artificial intelligence algorithm to analyze images for findings suggestive of pre-specified clinical conditions and promptly notifies the appropriate medical specialists of these findings in parallel with the standard of care image interpretation. Identification of suspected findings is not for diagnostic use beyond notification. Specifically, the device analyzes non-contrast CT images of the head to detect intracranial hemorrhage (ICH). The system sends a notification to a clinician that a suspected ICH has been identified and recommends a review of those images. Images can be previewed and compressed through a mobile application. Notified clinicians are responsible for viewing non-compressed images on a diagnostic viewer and engaging in appropriate patient evaluation and relevant discussion with a treating clinician before making care-related decisions or requests. JLK-ICH is limited to the analysis of imaging data and should not be used in lieu of full patient evaluation or relied upon to make or confirm the diagnosis.

JLK-ICH is a radiological computer-assisted triage and notification (CADt) software that adheres to the DICOM standard. The device functions as a Non-Contrast Computed Tomography (NCCT) processing module, providing triage and notification for suspected hemispheric intracranial hemorrhage (ICH). This software acts as a notificationonly, parallel workflow tool for hospital networks and trained clinicians, enabling the identification and communication of suspected patient images to relevant specialists, independent of the standard care workflow. JLK-ICH processes non-contrast computed tomography (NCCT) scans, prioritizing triage and notification for suspected hemispheric intracranial hemorrhaqe (ICH). The system utilizes advanced artificial intelligence to automatically analyze NCCT scans for indicators of ICH and promptly notify appropriate medical specialists of potential cases. JLK-ICH comprises an image analysis algorithm hosted on JLK servers and a mobile application for notification management. The Al/ML-based algorithm is designed to analyze NCCT of the head scans forwarded from CT scanners to the JLK servers. The mobile software module enables users to receive and toggle notifications for suspected ICH cases identified by the JLK-ICH Image Analysis Algorithm. Users can view a patient list and non-diagnostic CT scans through the mobile application. Image viewing through the mobile application interface is for non-diagnostic purposes only.

JLK-PWI is an image processing software package to be used by trained professionals, including but not limited to physicians and medical technicians. The software runs on a standard off-the-shelf computer or a virtual platform, such as VMware, and can be used to perform image viewing, processing, and analysis of Diffusion-weighted imaging (DWI) and Perfusion-weighted imaging (PWI) images for the brain from Magnetic Resonance Imaging (MRI) systems. Data and images are acquired through DICOM-compliant imaging devices. JLK-PWI provides both viewing and analysis capabilities for dynamic imaging datasets obtained through MRI protocols. The DWI analysis capabilities are used to analyze local water diffusion properties from diffusion-weighted MRI data. The PWI analysis capabilities are for analyzing dynamic imaging data, showing properties of changes in contrast over time. This functionality includes calculating parameters related to tissue flow (perfusion) and tissue blood volume.

JLK-PWI is image processing software designed to analyze Diffusion-weighted imaging (DWI) and Perfusionweighted imaging (PWI) images from Magnetic Resonance Imaging (MRI) scanners. The software calculates local water diffusion properties from DWI images and the perfusion area, which is a delayed perfusion area, using the analyzed perfusion map from PWI images. JLK-PWI can be used to communicate with a DICOM-compliant device or a PACS server to receive DWI and PWI images. The software is designed to automatically receive and analyze DWI and PWI images with DICOM image data. The analyzed diffusion and perfusion parameters, which are related to the tissue blood flow and volume, are written to the source DICOM and stored in the data storage. Medical professionals can review the analysis results through the implemented user interface (UI) or a connected PACS server.

JLK-CTP is an image processing software package to be used by trained professionals, including but not limited to physicians and medical technicians. The software runs on a standard "off-the-shelf" computer or a virtual platform, such as VMware, and can be used to perform image viewing, processing, and analysis of CT perfusion images for the brain. Data and images are acquired through DICOM compliant imaging devices. JLK-CTP provides both viewing and analysis capabilities for dynamic imaging datasets obtained through CT Perfusion protocols. The analysis is for visualization and examination of imaging data, revealing characteristics of contrast changes over time. This functionality includes the calculation of CT perfusion parameters associated with tissue flow (perfusion) and tissue blood volume.

JLK-CTP is image processing software designed to analyze CT perfusion (CTP) images. Using the analyzed perfusion map, the software calculates the volume of the reduced cerebral blood flow (CBF) area and the volume of the delayed Tmax area in the CTP images. JLK-CTP can be used to communicate with a DICOM-compliant device or a PACS server to receive CTP images. The software is designed to automatically receive and analyze a head CTP image with DICOM image data. The analyzed perfusion parametric maps, which are related to the tissue blood flow and volume, are written to the source DICOM and stored in the data storage. Users can review the analysis results through the implemented user interface (UI) or a connected PACS server.

JBS-LVO is a notification-only, parallel workflow tool for use by hospital networks and trained clinicians to identify and communicate images of specific patients to a specialist, independent of standard of care workflow. JBS-LVO uses an artificial intelligence algorithm to analyze images for findings suggestive of a pre-specified clinical condition and to notify an appropriate medical specialist of these findings in parallel to standard of care image interpretation. Identification of suspected positive findings is not for diagnostic use beyond notification. Specifically, the device analyzes CT angiogram images of the brain acquired in the acute setting and sends notifications to a neurovascular specialist that a suspected large vessel occlusion has been identified and recommends a review of those images. Images can be previewed through a mobile application. JBS-LVO is intended to analyze terminal ICA and MCA-M1 vessels for LVOs. Images that are previewed through the mobile application are compressed and for informational purposes only. They are not intended for diagnostic use beyond notification. The JBS-LVO device does not alter the original medical image. Notified clinicians are responsible for viewing non-compressed images on a diagnostic viewer and engaging in appropriate patient evaluation and relevant discussion with a treating physician before making care-related decisions or requests. JBS-LVO is limited to the analysis of imaging data and should not be used in-lieu of full patient evaluation or relied upon to make or confirm a diagnosis. Limitations: The device does not process scans containing metallic artifacts.

JBS-LVO is a radiological computer aided triage and notification (CAD) software package compliant with the DICOM standard. IBS-VV is a notification-only, parallel workflow tool for use by hospital networks and trained clinicians to analyze computed tomography angiography (CTA) images for findings suggestive of a suspected large vessel occlusion (LVO) and to notify an appropriate medical specialist of these findings in parallel to standard of care image interpretation. Specifically, JBS-LVO is optimized to evaluate occlusions of the intracranial carotid artery (ICA) and proximal middle cerebral artery (MCA-M1 segment). It is important to clarify that this quantification is solely used within the device's Al module to facilitation process. The output provided to heathcare professionals is stiritly a flag indicating the presence (positive) of an LVO, in accordance with regulatory guidelines. JBS-LVO is a combination of software modules that allow for detection and notification of patients with a suspected LVC. JBS-LVO consists of an algorithm and mobile application software module. The JBS-LVO Image Analysis Algorithm (LVO Detection Algorithm) is a locked, artificial intelligence (Al) software algorithm utilizing convolutional neural network (CNN) that analyzes CTA images of the brain for a suspected LVO. The LVO Detection Algorithm is hosted on the ILK-server and analyzes applicable CTA images of the brain that are acquired on CT scanners and are automatically transmitted to the ILK-server. Upon detection of a suspected LVO, the LVO notification module sends a notification of the suspected finding. The JBS-LVO notification functionality enable medical professionals and clinicians to preview compressed and informational images through via mobile application notification. Image viewing through the mobile application interface is for informational purposes only and is not for diagnostic use.