Siemens Aktiengesellschaft

Siemens Healthcare Gmbh

Siemens Medical Solutions USA, Inc.

Stefan Boehm

Martin Spahn

Peter Durlak

Tong Fang

Dorin Comaniciu

Bogdan Georgescu

Yunqiang Chen

Adrian Barbu

Ti-chiun Chang

Boris Stowasser

Gerhard Hahm

Markus Lendl

Sandra Martin

Michelle Xiao-Hong Yan

Vassilis Athitsos

A method is for providing a normalized image. The method includes receiving a non-normalized image including first pixels and non-normalized intensities, each of the first pixels being characterized by one of the non-normalized intensities. Furthermore, the method includes determining a subtraction histogram, the subtraction histogram being configured to map a first intensity to the difference between the relative frequency of the first intensity and the relative frequency of a second intensity, the first intensity being one of the non-normalized intensities and the second intensity being one of the non-normalized intensities. Furthermore, the method includes providing a normalized image including second pixels and normalized intensities based on the non-normalized image and based on the subtraction histogram, each of the second pixels being characterized by one of the normalized intensities.

Providing a normalized image

A method and system for intelligent digital subtraction is disclosed. The method and system for intelligent digital subtraction can be used in a roadmap application for a coronary intervention. A mask image is obtained with vessels highlighted by contrast media. A guide wire is inserted into the vessels, and a guide wire image is obtained. A direct subtraction image is generated from the guide wire image and the mask image. A reduced noise subtraction image is generated based on mutual image information between the subtraction image and the guide wire image and mutual image information between the subtraction image and the mask image.

Method and system for intelligent digital subtraction

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 system and method for populating a database with a set of image sequences of an object is disclosed. The database is used to detect localization of a guidewire in the object. A set of images of anatomical structures is received in which each image is annotated to show a guidewire, catheter, wire tip and stent. For each given image a Probabilistic Boosting Tree (PBT) is used to detect short line segments of constant length in the image. Two segment curves are constructed from the short line segments. A discriminative joint shape and appearance model is used to classify each two segment curve. A shape of an n-segment curve is constructed by concatenating all the two segment curves. A guidewire curve model is identified that includes a start point, end point and the n-segment curve. The guidewire curve model is stored in the database.

System and method for detecting and tracking a guidewire in a fluoroscopic image sequence

In a method for operating an imaging medical examination device ( ), an event of the undisturbed operation of the medical examination device ( ) automatically triggers a defect determination ( ) for determining a defective pixel possibly present in the image. The event is derived for example from a switch-on process, a calibration process and/or an examination process. Preferably, after the defect determination ( ), a correction process ( ) is automatically triggered if a defective pixel was detected. A medical examination device ( ) has a detection device ( ) for automatically determining a defective pixel possibly present in the image, in which case the detection device ( ) can be activated by an event of the undisturbed operation of the medical examination device. A correction device ( ) for automatically eliminating a defective pixel that has possibly been detected is preferably present.

Method for operating an image system of an imaging medical examination device and medical examination device

An X-ray diagnostic installation has an X-ray tube, a voltage generator, a planar solid state X-ray image converter for generating raw images, an image system and a playback device. The image system has a device for offset correction that acquires an offset image and stores it in a correction offset memory. The correction offset memory is preceded by a microphony detector that analyzes the current offset image for disturbances due to microphony and allows storage only of a current offset image, that is free of such disturbances.

X-ray diagnostic installation having a planar solid state X-ray image converter

In an X-ray diagnostic installation and correction method wherein comet artifacts in the unprocessed image can be corrected, a geometrical analysis of the comet artifacts is implemented, an estimated reference value is determined from the original signal using the analysis result, an estimated detail signal is determined from the original signal using the analysis result, and the comet artifacts are corrected on the basis of the estimated reference value and the estimated detail signal.

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Oberasbach, Germany

Stefan Boehm