Siemens Information Systems, Ltd.

Siemens Medical Solutions Usa, Inc.

General Electric Company

Siemens Computer Aided Diagnosis Ltd.

Siemens Computer Aided Diagnostics, Ltd.

Dinesh Mysore Siddu

Jonathan Stoeckel

Mausumi Acharyya

Sarang Lakare

Sivaramanivas Ramaswamy

Sandeep Kumar Dewangan

Alexandra Manevitch

Eliahu Ratner

Gopichand Katragadda

Sandesh Gupta

Sumit Chakravarty

A method for automatically detecting pulmonary embolism (PE) candidates within medical image data using an image processing device includes administering radiocontrast into a patient. A sequence of computed tomography (CT) images is acquired. A level of radiocontrast at a pulmonary artery trunk of the patient is determined. One or more PE candidates are detected within a pulmonary artery tree of the patient based on the determined level of radiocontrast at the pulmonary artery trunk. The one or more detected PE candidates are displayed.

Pulmonary emboli detection with dynamic configuration based on blood contrast level

A method of detecting blood vessel shadows in an anterior posterior x-ray radiograph comprising the steps of: generating candidate sub areas of the radiograph showing changes in contrast above a threshold level; supressing rib shadow edges; eliminating lung tissue shadow edges, and categorizing and eliminating nodule shadows.

Identifying blood vessels in lung x-ray radiographs

A method of detecting lung nodules in an anterior posterior x-ray radiograph comprising the steps of: generating candidate regions in image showing changes in contrast above a threshold level, and eliminating false positives by eliminating edges assignable to organs by: identifying edges; categorizing and eliminating rib edges; categorizing and eliminating lung tissue edges, and categorizing and eliminating blood vessels.

Identifying ribs in lung X-rays

A medical imaging system is used to recognize an internal structure from a three-dimensional image. The image includes image sub-volumes. An image sub-volume is selected using a non-linear search pattern. The selected image sub-volume is analyzed for the presence of the internal structure. The steps of selecting an image sub-volume using the non-linear search pattern and analyzing the selected sub-volume for the presence of the internal structure are repeated until the internal structure is found in an image sub-volume. Bounds of the internal structure are identified based on the location of the image sub-volume within which the internal structure is found.

System and method for automatic detection of internal structures in medical images

A method and apparatus for estimating a depth of a crack from ultrasound scan data are provided. The method includes mapping multiple amplitude responses from the ultrasound scan data, each mapped amplitude response being representative of a signal from one of the sensors. The method further includes locating multiple linear responses among the mapped amplitude responses, each linear response being an indicator of a reflected signal from the crack. One or more sensor that corresponds to the linear responses from a given crack is identified. The depth of the crack is estimated using data from the identified sensors.

Method and system for inspecting objects using ultrasound scan data

Growing community of inventors

Bengaluru, India

Dinesh Mysore Siddu