Ge Precision Healthcare LLC

Poonam Dalal

Gireesha Chinthamani Rao

Gopal Biligeri Avinash

Katelyn Rose Nye

Ravi Soni

Beth Ann Heckel

Zoltan Kiss

Lehel Ferenczi

Dibyajyoti Pati

Alec Joseph Baenen

Zita Herczeg

Chen Liu

Hongxu Yang

Balazs Peter Cziria

Pulak Goswami

Dennis Wei Zhou

An artificial intelligence (AI) lead marker detection system is employed either as a component of the X-ray imaging system or separately from the X-ray imaging system to scan post-exposure X-ray images to detect and insert various lead markers, to digitize information provided by the type and location of the lead marker, and to employ the marker information in different X-ray system workflow automations. The marker information obtained by the AI lead marker detection system can also provide useful data for use in downstream clinical and quality applications apart from the X-ray system, such as either AI or non-AI analytical applications.

X-ray lead marker detection system for x-ray imaging system

An image processing system is provided. The image processing system includes a display, a processor, and a memory. The memory stores processor-executable code that when executed by the processor causes receiving images of a region of interest of a patient with an enteric tube or line disposed within the region of interest, detecting the medical tube or line within the image, generating a combined image by combining the received images, and superimposing graphical markers on the combined image that indicate placement or misplacement of the enteric tube or line, and displaying the combined image on a display. In further aspects, a classification of the enteric tube or line (e.g., correctly placed tube present, malpositioned tube present, and so forth) and a detected positional change in the placement of the enteric tube or line may be determined and communicated to one or more clinicians. Additionally, the outputs of the image processing system may also be provided to facilitate triage of patients, helping prioritize which tube placements require further attention and in what order.

System and method for visualizing placement of a medical tube or line

An artificial intelligence (AI) X-ray image information detection and correction system is employed either as a component of the X-ray imaging system or separately from the X-ray imaging system to automatically scan post-exposure X-ray images to detect various types of information or characteristics of the X-ray image, including, but not limited to, anatomy, view, orientation and laterality of the X-ray image, along with an anatomical landmark segmentation. The information detected about the X-ray image can then be stored by the AI system in association with the X-ray image for use in various downstream X-ray system workflow automations and/or reviews of the X-ray image.

System and method for automatic detection and correction of anatomy, view, orientation and laterality in X-ray image for X-ray imaging system

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Brookfield, WI, United States of America

Poonam Dalal