Siemens Aktiengesellschaft

Siemens Corporate Research, Inc.

Michelle Xiao-Hong Yan

Tong Fang

Ti-chiun Chang

Peter Durlak

Martin Requardt

Stefan Boehm

Markus Lendl

Hans Schüll

Ke Huang

Yue M Lu

A method and system for detecting lymph nodes in multiple complementary magnetic resonance (MR) sequences is disclosed. Anatomical landmarks, such as blood vessels, are extracted in a first MR sequence, such as an MR angiography (MRA) image. A search area is defined in at least one second MR sequence, such as a T1 weighted VIBE image, based on the anatomical landmarks extracted the first MR sequence. Lymph nodes are then detected in the search area of the second MR sequence. The lymph nodes can be detected by segmenting the search area into homogenous regions and determining whether each region is a lymph node using feature analysis.

Method and system for lymph node detection using multiple MR sequences

A method and system for image quality assessment is disclosed. The image quality assessment method is a no-reference method for objectively assessing the quality of medical images. This method is guided by the human vision model in order to accurately reflect human perception. A region of interest (ROI) of medical image is divided into non-overlapping blocks of equal size. Each of the blocks is categorized as a smooth block, a texture block, or an edge block. A perceptual sharpness measure, which is weighted by local contrast, is calculated for each of the edge blocks. A perceptual noise level measure, which is weighted by background luminance, is calculated for each of the smooth blocks. A sharpness quality index is determined based on the perceptual sharpness measures of all of the edge blocks, and a noise level quality index is determined based on the perceptual noise level measures of all of the smooth blocks. An overall image quality index can be determined by using task specific machine learning of samples of annotated images. The image quality assessment method can be used in applications, such as video/image compression and storage in healthcare and homeland security, and band-width limited wireless communication.

Method and system for human vision model guided medical image quality assessment

A method for optic disk detection in retinal images, includes: extracting a vessel tree from a retinal image; locating an optic disk in the retinal image using the vessel tree; enhancing a contrast of the optic disk; removing vessels from the contrast enhanced optic disk; detecting a boundary of the optic disk with vessels removed by generating an edge map; projecting the edge map at a plurality of angles by using a radon transform; and estimating a radius and center of the optic disk using the projections.

System and method for robust optic disk detection in retinal images using vessel structure and radon transform

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Princeton, NJ, United States of America

Michelle Xiao-Hong Yan