Siemens Information Systems, Ltd.

Siemens Medical Solutions Usa, Inc.

Siemens Computer Aided Diagnosis Ltd.

Siemens Computer Aided Diagnostics, Ltd.

Mausumi Acharyya

Jonathan Stoeckel

Dinesh Mysore Siddu

Alexandra Manevitch

Eliahu Ratner

Sumit Chakravarty

Sandesh Gupta

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

Detected lung nodules are presented in a chest radiographic sub-image. A curve is matched to pixels in the sub-image and confidence values for individual pixels is determined. A confidence image is generated consisting of the confidence values at the position of the respective pixel. Separated regions of pixels within the confidence image are identified which have a confidence value greater than a threshold confidence value. A filtered confidence image is generated consisting of the separated regions of the confidence image which are larger than a threshold area. A histogram of values characteristic for the matching of the curve is determined, wherein the filtered confidence image is used as a mask, such that only values are considered for the histogram which correspond to the separated regions of the filtered confidence image. A statistical measure of the histogram is determined and the lung nodules are verified based on the statistical measure.

Method and system for verifying detection of a lung nodule

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.

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Bengaluru, India

Mausumi Acharyya