Koninklijke Philips Corporation N.v.

Rapiscan Systems, Inc.

Samsung Electronics Co., Ltd.

Karthik Krishnan

Pallavi Vajinepalli

Celine Firtion

Thomas Brown

Subhendu Seth

Matthew Rielly

Mala Sivakumar

Giridhar Narasapura Rajagopalaiah

David N Roundhill

Soumabha Bhowmick

Saunak Chatterjee

Robert Gustav Trahms

Earl M Canfield, Ii

Sejin Yoo

Hyunhee Jo

Bhavya Ajani

Karthik Raj Katipally

There is proposed a mechanism for determining whether or not an imaging probe, such as an ultrasound imaging probe, is at a desired orientation and/or position with respect to an anatomical structure. Image data of the imaging probe is processed to generate a 3D landmark model that contains anatomical landmarks of the anatomical structure. The 3D landmark model is then processed to determine whether or not the imaging probe is at the desired orientation and/or position.

Guided acquisition of a 3D representation of an anatomical structure

A mechanism for automatically generating and ranking M-mode lines for generating or defining M-mode data usable to assess fetal heart activity, e.g. determine a fetal heart rate. A region of interest, containing a fetal heart, in a sequence of ultrasound images is identified. The region of interest is used to define the position of each of a plurality of M-mode lines, e.g. anatomical M-mode lines. A quality measure of each M-mode line is determined based on M-mode data generated for each M-mode line, and the quality measures are then used to rank the M-mode lines.

Generation of M-mode data for detecting fetal cardiac activity

In some embodiments, the present specification describes methods for displaying a three-dimensional image of an isolated threat object or region of interest with a single touch or click and providing spatial and contextual information relative to the object, while also executing a view dependent virtual cut-away or rendering occluding portions of the reconstructed image data as transparent. In some embodiments, the method includes allowing operators to associate audio comments with a scan image of an object. In some embodiments, the method also includes highlighting a plurality of voxels, which are indicative of at least one potential threat item, in a mask having a plurality of variable color intensities, where the intensities may be varied based on the potential threat items.

Methods and systems for generating three-dimensional images that enable improved visualization and interaction with objects in the three-dimensional images

There is proposed a mechanism for generating and displaying a 3D representation of an anatomical structure of an individual. Image data of the anatomical structure is obtained and processed to obtain 2D images or image sequences corresponding to predetermined views of the anatomical structure. Anatomical landmarks are identified in the 2D images or image sequences and used to determine a 3D landmark model of the anatomical 5 structure. The 3D landmark model is used to render and display a 3D representation of the anatomical structure.

Rendering and displaying a 3D representation of an anatomical structure

The invention relates to a computer-implemented method for automatically detecting anatomical structures () in a medical image () of a subject, the method comprising applying an object detector function () to the medical image, wherein the object detector function performs the steps of: (A) applying a first neural network () to the medical image, wherein the first neural network is trained to detect a first plurality of classes of larger-sized anatomical structures (), thereby generating as output the coordinates of at least one first bounding box () and the confidence score of it containing a larger-sized anatomical structure; (B) cropping () the medical image to the first bounding box, thereby generating a cropped image () containing the image content within the first bounding box (); and (C) applying a second neural network () to the cropped medical image, wherein the second neural network is trained to detect at least one second class of smaller-sized anatomical structures (), thereby generating as output the coordinates of at least one second bounding box () and the confidence score of it containing a smaller-sized anatomical structure.

Method and system for automatically detecting anatomical structures in a medical image

A computer-implemented method for visualization of an elongated anatomical structure (), for example of a fetal spine using ultrasound is provided. The method comprising the steps of: receiving a plurality of 3D ultrasound image volumes, each image volume depicting at least a portion of an elongated anatomical structure (); on each 3D ultrasound image volume, automatically or semi-automatically fitting a parametric curve () to the depicted portion of the elongated anatomical structure, the parametric curve being defined by curve parameters; reformatting each 3D ultrasound image volume by applying a transformation which straightens the parametric curve along at least one axis, so as to generate a plurality of reformatted image volumes and reformatted parametric curves (); registering the reformatted image volumes with one another by determining the joining point of their respective parametric curves; and fusing the reformatted image volumes with one another to yield a fused image depicting the whole elongated anatomical structure or a larger portion thereof than the 3D ultrasound image volumes.

Computer-implemented method for visualization of an elongated anatomical structure

Unoccluded visualization of Anatomy in Volumetric Data. Embodiments disclosed herein relate to medical imaging systems, and more particularly to medical visualization systems, which can be used for visualizing anatomy. Embodiments herein disclose methods and systems for enabling unoccluded visualization of anatomy of interest in volumetric data. Embodiments herein disclose 3D visualization techniques for visualization of deep seated anatomy with no user interactions, while preserving depth continuity with surrounding(s) and with minimal distortion for improved clinical assessment.

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Bengaluru, India

Karthik Krishnan