Gen-probe, Inc.

Siemens Healthcare Diagnostics Gmbh

Siemens Aktiengesellschaft

Siemens Healthcare Gmbh

Friedrich-Alexander-Universitat Erlangen-Nürnberg

Wen Wu

Terrence Chen

Jeffrey M Linnen

Norbert Strobel

Benjamin S Pollack

Yao-Jen Chang

Dorin Comaniciu

Michael McClellan Becker

Kui Gao

Reinhold B Pollner

Alexander Brost

Paul M Darby

Guillaume Dumont

Stefan Kluckner

Martin Ostermeier

Shaohua Kevin Zhou

Atilla Peter Kiraly

David D Liu

Rui Liao

Gareth Funka-Lea

Joachim Hornegger

Andreas Wimmer

Peng Wang

Anton Nekovar

Patrick Wissmann

Lei Zhang

Martin Willibald Koch

JinHyeong Park

Khurram Soomro

Sebastian Kaeppler

Geoffrey G Dennis

Reinhold P Pollner

Jinhyeong Park

Jeffery Linnen

Jeffery M Linnen

A model-based method of inspecting a specimen for presence of one or more interferent, such as Hemolysis, Icterus, and/or Lipemia (HI L) is provided. The method includes generating a pixelated image of the specimen in a first color space, determining color components (e.g., an a-value and a b-value) for pixels in the pixelated image, classifying of the pixels as being either liquid or non-liquid, defining one or more liquid regions based upon the pixels classified as liquid, and determining a presence of one or more interferent within the one or more liquid regions. The liquid classification is based upon a liquid classification model. Pixel classification may be based on a trained multiclass classifier. Interference level for the one or more interferent may be provided. Testing apparatus adapted to carry out the method are described, as are other aspects.

Model-based methods and apparatus for classifying an interferent in specimens

Barcode tag conditions on sample tubes are detected utilizing side view images of sample tubes for streamlining handling in clinical laboratory automation systems. The condition of the tags may be classified into classes, each divided into a list of additional subcategories that cover individual characteristics of the tag quality. According to an embodiment, a tube characterization station (TCS) is utilized to obtain the side view images. The TCS enables the simultaneous or near-simultaneous collection of three images for each tube, resulting in a 360 degree side view for each tube. The method is based on a supervised scene understanding concept, resulting in an explanation of each pixel into its semantic meaning. Two parallel low-level cues for condition recognition, in combination with a tube model extraction cue, may be utilized. The semantic scene information is then integrated into a mid-level representation for final decision making into one of the condition classes.

Barcode tag detection in side view sample tube images for laboratory automation

A method of tube slot localization is provided using a tray coordinate system and a camera coordinate system. The method includes receiving, a series of images from at least one camera of a tray comprising tube slots arranged in a matrix of rows and columns. Each tube slot is configured to receive a sample tube. The method also includes automatically detecting fiducial markers disposed on cross sectional areas between the tube slots on the tray and receiving an encoder value indicating when each row of the tray is substantially at the center of the camera's field of view. The method further includes determining calibration information to provide mapping of locations from the tray coordinate system to locations from the camera coordinate system and automatically aligning the tray based on the encoder value and calibration information.

Image-based tray alignment and tube slot localization in a vision system

A method and system for motion estimation modeling for cardiac and respiratory motion compensation is disclosed. Specifically, a coronary sinus catheter is tracked in a plurality of frames of a fluoroscopic image sequence; and cardiac and respiratory motion of a left atrium is estimated in each of the plurality of frames based on tracking results of the coronary sinus catheter using a trained motion estimation model.

Method and system for motion estimation model for cardiac and respiratory motion compensation

Embodiments are directed to classifying barcode tag conditions on sample tubes from top view images to streamline sample tube handling in advanced clinical laboratory automation systems. The classification of barcode tag conditions leads to the automatic detection of problematic barcode tags, allowing for a user to take necessary steps to fix the problematic barcode tags. A vision system is utilized to perform the automatic classification of barcode tag conditions on sample tubes from top view images. The classification of barcode tag conditions on sample tubes from top view images is based on the following factors: (1) a region-of-interest (ROI) extraction and rectification method based on sample tube detection; (2) a barcode tag condition classification method based on holistic features uniformly sampled from the rectified ROI; and (3) a problematic barcode tag area localization method based on pixel-based feature extraction.

Classification of barcode tag conditions from top view sample tube images for laboratory automation

A method for detecting properties of sample tubes is provided that includes extracting image patches substantially centered on a tube slot of a tray or a tube top in a slot. For each image patch, the method may include assigning a first location group defining whether the image patch is an image center, a corner of an image or a middle edge of an image, selecting a trained classifier based on the first location group and determining whether each tube slot contains a tube. The method may also include assigning a second location group defining whether the image patch is from an image center, a left corner of the image, a right corner of the image, a left middle of the image; a center middle of the image or a right middle of the image, selecting a trained classifier based on the second location group and determining a tube property.

Locality-based detection of tray slot types and tube types in a vision system

Embodiments provide a method of using image-based tube top circle detection that includes extracting, from one of a series of images of a tube tray, a region of interest (ROI) patch having a target tube top circle and boundaries constrained by two dimensional (2D) projections of different types of tube top circle centers. The method also includes calculating an edge gradient magnitude map of the ROI patch and constructing a three dimensional (3D) map of a circle parameter space, each location in the 3D map corresponding to a circle parameter having a center location and a diameter. The method further includes accumulating weighted votes in the 3D map from edge points in the edge gradient magnitude map along edge point gradient directions, determining locations in the 3D map as circle candidates based on the accumulated votes and selecting a target tube top circle based on the greatest accumulated votes.

Image-based tube slot circle detection for a vision system

A method for real-time collimation and ROI-filter positioning in X-ray imaging in interventional procedures includes acquiring an image of a region-of-interest (ROI) at a beginning of a medical intervention procedure on a subject, classifying the image based on low-level features in the image to determine a type of procedure being performed, determining a list of landmarks in the image from the type of procedure being performed, and loading a pre-trained landmark model for each landmark in the list of landmarks, where landmarks include anatomical structures of the subject and medical devices being used in the medical intervention procedure, and computing collimator settings of an X-ray imaging device from ROI filter margins and bounding boxes of the landmarks calculated using the landmark models.

Real-time collimation and ROI-filter positioning in X-ray imaging via automatic detection of the landmarks of interest

Methods and systems for detecting properties of sample tubes in a laboratory environment include a drawer vision system that can be trained and calibrated. Images of a tube tray captured by at least one camera are analyzed to extract image patches that allow a processor to automatically determine if a tube slot is occupied, if the tube has a cap, and if the tube has a tube top cup. The processor can be trained using a random forest technique and a plurality of training image patches. Cameras can be calibrated using a three-dimensional calibration target that can be inserted into the drawer.

Drawer vision system

A computer-implemented method for tracking one or more objects in a sequence of images includes generating a dictionary based on object locations in a first image included in the sequence of images. One or more object landmark candidates are identified in the sequence of images and a plurality of tracking hypothesis for the object landmark candidates are generated. A first tracking hypothesis is selected from the plurality of tracking hypothesis based on the dictionary.

Robust multi-object tracking using sparse appearance representation and online sparse appearance dictionary update

A method and system for detecting and tracking multiple catheters in a fluoroscopic image sequence in an integrated central processing unit and graphics processing unit framework is disclosed. A catheter electrode model is initialized in a first frame of the fluoroscopic image sequence. The catheter landmark candidates are detected, by a graphics processing unit, in the first frame of the fluoroscopic image sequence. The catheter electrode model is tracked, by a central processing unit, and is detected by the graphics processing unit, in subsequent frames of the fluoroscopic image sequence by detecting catheter landmark candidates in the subsequent frames of the fluoroscopic image sequence using at least one trained catheter landmark detector, and outputting the catheter model tracking and landmark detection results of for each frame of the fluoroscopic image sequence.

Method and system for tracking catheters in 2D X-ray fluoroscopy using a graphics processing unit

A method for compensating cardiac and respiratory motion in atrial fibrillation ablation procedures includes (a) simultaneously determining a position of a circumferential mapping (CFM) catheter and a coronary sinus (CS) catheter in two consecutive image frames of a series of first 2-D image frames; (b) determining a distance between a virtual electrode on the CS catheter and a center of the CFM catheter for a first image frame of the two consecutive image frames, and for a second image frame of the two consecutive image frames; and (c) if an absolute difference of the distance for the first image frame and the distance for the second image frame is greater than a predetermined threshold, compensating for motion of the CFM catheter in a second 2-D image.

Combined cardiac and respiratory motion compensation for atrial fibrillation ablation procedures

A method () and system () for performing real-time, dynamic overlays on fluoroscopic images to aid in navigation and localization during medical procedures.

Method for performing dynamic registration, overlays, and 3D views with fluoroscopic images

A method and system for tracking an ablation catheter and a circumferential mapping catheter in a fluoroscopic image sequence is disclosed. Catheter electrode models for the ablation catheter and the circumferential mapping catheter are initialized in a first frame of a fluoroscopic image sequence based on user inputs. The catheter electrode models for the ablation catheter and the circumferential mapping catheter are then tracked in each remaining frame of the fluoroscopic image sequence. In each remaining frame, candidates of catheter landmarks such as the catheter tip, electrodes and body points are detected for the ablation catheter and the circumferential mapping catheter, tracking hypotheses for the catheter electrode models are generated, and for each of the ablation catheter and the circumferential mapping catheter, the catheter electrode model having the highest probability score is selected from the generated tracking hypotheses.

Method and system for ablation catheter and circumferential mapping catheter tracking in fluoroscopic images

A method and system for detecting and tracking coronary sinus (CS) catheter electrodes in a fluoroscopic image sequence is disclosed. An electrode model is initialized in a first frame of the fluoroscopic image sequence based on input locations of CS sinus catheter electrodes in the first frame. The electrode model is tracked in subsequent frames of the fluoroscopic image sequence by detecting electrode position candidates in the subsequent frames of the fluoroscopic image sequence using at least one trained electrode detector, generating electrode model candidates in the subsequent frames based on the detected electrode position candidates, calculating a probability score for each of the electrode model candidates, and selecting an electrode model candidate based on the probability score.

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Kirkland, WA, United States of America

Wen Wu