Siemens Medical Solutions Usa, Inc.

Siemens Aktiengesellschaft

Siemens Corporation

Siemens Corporate Research, Inc.

Rensselaer Polytechnic Institute

Siemens Medical Soultions Usa, Inc.

Hong Shen

Shuping Qing

Lin Hong

Atilla Peter Kiraly

Benjamin L Odry

Christopher Vincent Alvino

Jianzhong Qian

Li Fan

Ying Li

Yonggang Shi

Michael Shur

Gregory G Slabaugh

Gozde Unal

Limin Ma

Yumao Lu

Bernhard Göbel

Tor Fjeldly

Andrew Litvin

Lichen Liang

A system and method for enhanced viewing of rib metastasis in CT volume data is disclosed. The system and method receive input CT volume data and display slices of the CT volume data. Ribs are automatically segmented from the CT volume data, ordered and labeled. A 3D visualization of the ribs is generated and displayed. Alterations in the rib structure is automatically detected using shape based analysis of the ribs. The alterations are marked as candidate locations for rib metastasis in the displayed slices and 3D visualization in order to assist in the diagnosis of rib metastasis.

System and method for enhanced viewing of rib metastasis

A computer-implemented method for combinational computer aided diagnosis (C-CAD) includes providing volume data of tissue, providing a database of disease and pathologies, and providing action items for processing the volume data. The method further comprises selecting at least two diseases of interest for the volume data, selecting at least one action item to be performed for each selected disease, determining a set of decision rules based on an output of a selected action item, and producing a combinational report predicting of the tissue of the volume data.

Combinational computer aided diagnosis

A method and system for visualizing the spine in 3D medical images is disclosed. A spinal cord centerline is automatically determined in a 3D medical image volume, such as a CT volume. A reformatted image volume is then generated based on the spinal cord centerline. The reformatted image volume can be a straightened spine volume or a Multi-planar Reconstruction (MPR) based volume that follows the natural curve of the spine. The reconstructed volume can be displayed as 2D slices or 3D volume renderings.

Method and system for spine visualization in 3D medical images

A method and system for nodule feature extract using background contextual information in chest x-ray images is disclosed. In order to detect false positives in nodule candidates for a chest x-ray image, background contextual information, such as contextual vessel tree information, is defined in the chest x-ray image. Features are extracted for each nodule candidate based on the background contextual information, and the extracted features are used to detect whether each nodule candidate is a false positive or a genuine nodule.

Method and system for nodule feature extraction using background contextual information in chest x-ray images

A method for directed machine learning includes receiving features including intensity data and location data of an image, condensing the intensity data and the location data into a feature vector, processing the feature vector by a plurality of classifiers, each classifier trained for a respective trained class among a plurality of classes, outputting, from each classifier, a probability of the feature vector belong to the respective trained class, and assigning the feature vector a label according to the probabilities of the classifiers, wherein the assignment produces a segmentation of the image.

Machine learning for tissue labeling segmentation

Disclosed is a method and apparatus for registering data points in data sets representing scan data. Data points corresponding to a physical feature represented in the scan data are automatically detected. The detected data points in one data set are correlated with detected data points in another data set. A group of similarity transformations between the correlated detected data points is then calculated. The group of similarity transformations is then combined. In one advantageous embodiment, the physical feature is vertebras.

Method and system for registering CT data sets

A method and system for automatically detecting rib metastasis in a thoracic CT volume is disclosed. The ribs are segmented in said CT volume by recursive tracing. A series of cross-sectional images are then generated along a centerline of each rib. Cortical and trabecular bone structures are segmented in each of the cross-sectional images for each rib. Features are calculated for each cross-sectional image based on characteristics of the cortical and trabecular bone structures, and alterations are detected in the cross-sectional images based on the features. Rib metastasis is detected in a rib when an alteration is detected in a number of consecutive cross-sectional images along the centerline of the rib.

System and method for automatic detection of rib metastasis in computed tomography volume

Feature processing is provided for lung nodules in computer-assisted diagnosis. A feature that may better distinguish nodules from background is extracted using a Hough transform. Rather than relying on a specific boundary shape, the Hough transform accumulates evidence associated with a region, such as a ring region. The accumulated evidence provides a feature score without requiring a nodule to fit a specific shape. In another approach, a background level is determined from extracted features. Rather than attempting to normalize an image prior to extraction, the features are normalized. The feature normalization and generalized Hough transform extraction may be used together or alone.

Feature processing for lung nodules in computer assisted diagnosis

A method and system for locating an opaque region, such as a heart region in a chest X-ray radiograph is disclosed. In order to segment a heart region in a chest X-ray radiograph, a heart region boundary is generated based on lung boundaries in the chest X-ray radiograph and an average heart region model. A location of the lower boundary of the heart region in the chest X-ray radiograph is then determined. Left and right portions of the heart region boundary are independently registered to corresponding portions of the lung boundaries, and upper and lower portions of the heart region boundary are adjusted based on the left and right portions in order to form a smooth contour.

Method and system for locating opaque regions in chest X-ray radiographs

A method for performing computer-assisted lesion assessment includes acquiring contrast enhanced MRI data. A region of interest is identified. Kinetic properties, morphological properties and pattern of enhancement are determined for the identified region of interest. A score is calculated for each of the kinetic properties, morphological properties, pattern of enhancement. A cumulative score is calculated for the identified region of interest. The scores are provided to a medical practitioner to assist in diagnosing the identified region of interest.

Computer aided lesion assessment in dynamic contrast enhanced breast MRI images

A method and system for segmenting diaphragm regions in a chest X-ray radiograph is disclosed. The diaphragm regions are segmented based on left and right lung lobe regions and a heart region in the chest X-ray radiograph. A right diaphragm region is segmented in the chest X-ray radiograph based a boundary of the right lung lobe. A left diaphragm region is segmented in the chest X-ray radiograph based on the heart region and a boundary of the left lung lobe.

Method and system for diaphragm segmentation in chest X-ray radiographs

A method for tracing, rib posteriors includes providing an incomplete rib tracing comprising a digitized 3-dimensional representation of a rib and a digital image from which said rib tracing was extracted, initializing, a tracing direction for a remainder of said rib, detecting a plurality of ridge points in a sub-volume of said digital image about said initial tracing direction, and deforming a closed curve in a plane perpendicular to said tracing direction until a rib-edge contour is obtained, using said ridge points as constraints.

System and method for tracing rib posterior in chest CT volumes

A method for analyzing a medical image. The process: establishes a predetermined criteria; obtains data in a plane traverse the anatomical object; identifies a point disposed on the object in the plane; detects contour points of the object in the plane from the identified point; analyzes the obtained contour points to predict a subsequent point on the object and a tracing direction, such tracing direction being along the length of the object; determines a subsequent plane transverse the object, such predicted point being in the subsequent plane; repeats the process until the predetermined criterion is satisfied.

Method for analyzing medical image data

Disclosed is a systematic way of automatically segmenting lung regions. To increase the efficiency of a lung segmentation technique, a region-based technique, such as region growing, is performed by a computer on a middle slice of the CT volume. A contour-based technique is then used for a plurality of non-middle slices of the CT volume. This allows the implementation to be multithreaded and results in an improvement in the segmentation algorithm's efficiency.

Method and system for automatic lung segmentation

A method for cardiac segmentation includes providing a plurality of digitized medical images, each image comprising a plurality of intensities corresponding to a domain of points on an 2-dimensional grid, the plurality of images forming a sequence of cardiac images acquired at different time points, filtering noise from the sequence of images, approximating the endocardium with a first circle, approximating the epicardium with a second circle, finding candidate points for the endocardium, finding candidate points for the epicardium, and interpolating gaps between points of the endocardium and between points of the epicardium wherein the myocardium is segmented.

Growing community of inventors

Plainsboro, NJ, United States of America

Hong Shen