General Electric Company

Suvadip Mukherjee

Rakesh Mullick

Christian Fritz Perrey

Roshni Bhagalia

Nitin Singhal

Xiaojie Huang

A system (e.g., an ultrasound imaging system) is provided. The system includes an ultrasound probe configured to acquire three-dimensional (3D) ultrasound data of a volumetric region of interest (ROI). The system further includes a display, a memory configured to store programmed instructions, and a controller circuit. The controller circuit includes one or more processors. The controller circuit is configured to execute the programmed instructions stored in the memory. When executing the programmed instructions, the controller circuit performs a plurality of operations. The operations includes collecting the 3D ultrasound data from an ultrasound probe and identifying a select set of the 3D ultrasound data corresponding to an object of interest within the volumetric ROI. The operations further include segmenting the object of interest from the select set of the 3D ultrasound data, generating a visualization plane of the object of interest, and displaying the visualization plane on the display.

Method and system for generating a visualization plane from 3D ultrasound data

Embodiments described herein provide a hybrid technique which incorporates learned pulmonary nodule features in a model based energy minimization segmentation using graph cuts. Features are extracted from training samples using a convolutional neural network, and the segmentation cost function is augmented via the deep learned energy. The system and method improves segmentation performance and more robust initialization.

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Bengaluru, India

Suvadip Mukherjee