Eastman-kodak Company

Carestream Health, Inc.

Henry Nicponski

Lawrence Allen Ray

Richard Alan Simon

Edward B Gindele

Shoupu Chen

David R Cok

Tomasz A Matraszek

Mark R Bolin

A method and a system are disclosed for labeling an anatomical point associated with a lesion in an organ such as a lung. The method includes: a segmentation of a vessel tree anatomical structure starting from an autonomously determined initial image point; labeling the vessel segments of the vessel tree segmentation with segment labels based on a priori anatomical knowledge, thereby creating an individualized anatomical model; receiving a user-specified image point having a location from a user and locating a nearby vessel structure; tracking along the vessel structure in a direction towards a root of a parent vessel tree until a prior labeled vessel segment is encountered in the anatomical model, and assigning the label of the encountered prior labeled vessel segment from the anatomical model as an anatomical location label of the user-specified image point.

Method for lung lesion location identification

A computer aided disease detection system and method for multiple organ systems. The method performs computer aided examination of digital medical images. A patient exam type of a digital medical image is determined. Based on the patient exam type, one or more of a plurality of knowledge based anatomical segmentation blocks are invoked, each block performing image segmentation for a single organ or organ system present in the image. Based on the patient exam type, for each successfully segmented organ or organ system, one or more of a plurality of knowledge based computer aided detection blocks are invoked, each block of which is designed to search for and locate potential disease foci in a particular organ or organ system.

Computer aided disease detection system for multiple organ systems

A method for determining the presence of a face from image data utilizes at least first and second algorithms. The first algorithm prescreens the image data, by determining a plurality of face candidates utilizing a pattern matching technique that identifies image windows likely to contain faces based on color and shape information. The second algorithm processes the face candidates determined by the first algorithm, and uses a posterior probability function classifier to determine the presence of the face.

Face detecting camera and method

A digital image processing method for detecting faces in a digital color image comprises the steps of: providing a distributed face detection system having complementary classifiers, wherein the classifiers are complementary in a frequency domain; selecting classifier parameters for the complementary classifiers from a plurality of different parameter generating sources, at least one of which is controllable by human input; reconfiguring the complementary classifiers in the distributed face detection system according to the selected classifier parameters; and detecting faces using the distributed face detection system.

Method and system for face detection in digital images

In methods, systems, and computer program products for locating a regularly configured object within a digital image, a plurality of primary rotated integral images of the digital image are computed. Each primary rotated integral image has a different in-plane rotation. A set of secondary rotated integral images are derived from each of the primary rotated integral images. The secondary rotated integral images have further in-plane rotations relative to the respective primary rotated integral image. A window is defined within the digital image and corresponding windows of the rotated integral images. The values of convolution sums of a predetermined set of feature boxes within the window, in each of the rotated integral images are extracted. The dimensionality of the convolution sums is reduced to provide a set of reduced sums. A probability model is applied to the reduced sums to provide a best estimated derotated image of the window.

In-plane rotation invariant object detection in digitized images

A retouching method for enhancing an appearance of a face located in a digital image involves acquiring a digital image containing one or more faces and detecting a location of facial feature points in the faces, where the facial feature points include points identifying salient features such as skin, eyes, eyebrows, nose, mouth, and hair. The location of the facial feature points are used to segment the face into different regions such as skin, eyes, eyebrows, nose, mouth, neck and hair regions. Facially relevant characteristics of the different regions are determined and, based on these facially relevant characteristics, an ensemble of enhancement filters are selected, each customized especially for a particular region, and the default parameters for the enhancement filters are selected. The enhancement filters are then executed on the particular regions, thereby producing an enhanced digital image from the digital image.

Method and system for enhancing portrait images

In a method for determining the general semantic theme of a group of images, whereby each digitized image is identified as belonging to a specific group of images, one or more image feature measurements are extracted from each of the digitized images in an image group, and then used to produce an individual image confidence measure that an individual image belongs to one or more semantic classifications. Then, the individual image confidence measures for the images in the image group are used to produce an image group confidence measure that the image group belongs to one or more semantic classifications, and the image group confidence measure is used to decide whether the image group belongs to one or to none of the semantic classifications, whereby the selected semantic classification constitutes the general semantic theme of the group of images. Additionally, a plurality of semantic theme processors, one for each semantic classification, are provided to produce enhanced value imaging services and products for image groups that fall into an appropriate semantic theme.

Method and system for processing images for themed imaging services

A method for determining the presence of a face from image data includes a face detection algorithm having two separate algorithmic steps: a first step of prescreening image data with a first component of the algorithm to find one or more face candidate regions of the image based on a comparison between facial shape models and facial probabilities assigned to image pixels within the region; and a second step of operating on the face candidate regions with a second component of the algorithm using a pattern matching technique to examine each face candidate region of the image and thereby confirm a facial presence in the region, whereby the combination of these components provides higher performance in terms of detection levels than either component individually. In a camera implementation, a digital camera includes an algorithm memory for storing an algorithm comprised of the aforementioned first and second components and an electronic processing section for processing the image data together with the algorithm for determining the presence of one or more faces in the scene. Facial data indicating the presence of faces may be used to control, e.g., exposure parameters of the capture of an image, or to produce processed image data that relates, e.g., color balance, to the presence of faces in the image, or the facial data may be stored together with the image data on a storage medium.

An electronic reproduction apparatus is provided with a modeling routine that includes the steps of identifying a portion of an electronic image to be modified; defining an optical axis, a projection point, a density contour shape and a density gradient profile within the portion of the electronic image to be modified; and calculating modified image data values based on the optical axis, projection point, density contour shape and density gradient profile; applying the modified image data values the portion of the electronic image to be modified. The modified image data is calculated using a cubic spline interpolation. The modeling routine enables the production of smooth and natural contours and gradients required to create common enhancement effects such as shadows, glows, highlights and vignettes.

Method and apparatus for modifying electronic image data

An improved airbrush modeling routine is disclosed that can be implemented in a conventional electronic image reproduction system. The improved airbrush modeling routine incorporates an interpolation function with velocity smoothing to provide improved sampling of brush location during airbrushing operations by calculating the average velocity between sample intervals and determining average acceleration. In addition, randomness is introduced in the improved airbrush modeling routine to provide for a 'textured' appearance in a retouched area of an original image.

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Albion, NY, United States of America

Henry Nicponski