The State University of New York

William H Moore

Zhengrong Liang

Jerome Zhengrong Liang

Jianhua Ma

Huafeng Wang

Bowen Song

Lukasz Krzeminski

Zhigang Xu

Hao Zhang

Yu Zhou

Hao Han

Jerome Zheng Liang

Kaarvannan Thiruvalluvan

FangFang Han

An image-guided system and method for performing needle biopsy on a moving lung nodule of a body is provided. CT images of the lung nodule are obtained to generate a motion model, based on which an optimal needle advancing path is determined. The motion of the lung nodule and the motion of a fiducial marker attached to the body are correlated. The motion of the fiducial marker is tracked and monitored by a camera to determine a position of the lung nodule based on the correlation. A time for advancing the needle is determined based on a motion attribute of the reference. The needle is advanced by a robotic needle manipulator at the predetermined time along the path to accomplish the needle placement.

System and method for CT-guided needle biopsy

Provided are an apparatus and method for fast and adaptive computer-aided detection of pulmonary nodules and differentiation of malignancy from benignancy in thoracic CT images using a hierarchical vector quantization scheme. Anomalous pulmonary nodules are detected by obtaining a two-dimensional (2D) feature model of a pulmonary nodule, segmenting the pulmonary nodule by performing vector quantification to expand the 2D feature model to a three-dimensional (3D) model, and displaying image information representing whether the pulmonary nodule is benign, based upon the 3D model expanded from the 2D feature model, with duplicate information eliminated by performing feature reduction performed using a principal component analysis and a receiver operating characteristics area under the curve merit analysis. A textural feature analysis detects an anomalous pulmonary nodule, and 2D texture features are calculated from 3D volumetric data to provide improved gain compared to calculation from a single slice of 3D data.

Method for adaptive computer-aided detection of pulmonary nodules in thoracic computed tomography images using hierarchical vector quantization and apparatus for same

Disclosed is a method for performing X-ray Computed Tomography scanning, the method including acquiring a plurality of images of an object, obtaining an initial image from the plurality of images, calculating NonLocal weight of the initial image, utilizing a current image estimation and registered prior image, performing a successive over-relaxation optimization to yield a new image estimation with an intensity of the new image estimation equal or greater than zero, performing a cycle update, generating an image of the object utilizing the new image estimation obtained from the optimization, and outputting a resultant image.

Iterative reconstruction for X-ray computed tomography using prior-image induced nonlocal regularization

Growing community of inventors

Setauket, NY, United States of America

William H Moore