Methods include processing image data through a plurality of network stages of a progressively holistically nested convolutional neural network, wherein the processing the image data includes producing a side output from a network stage m, of the network stages, where m>1, based on a progressive combination of an activation output from the network stage m and an activation output from a preceding stage m1. Image segmentations are produced. Systems include a 3D imaging system operable to obtain 3D imaging data for a patient including a target anatomical body, and a computing system comprising a processor, memory, and software, the computing system operable to process the 3D imaging data through a plurality of progressively holistically nested convolutional neural network stages of a convolutional neural network.

In a medical image processing apparatus, a medical image processing method, and a medical image processing program, in a case where there are a plurality of past brain images, it is possible to select a past brain image with which the atrophy rate of the brain can be accurately calculated. An image acquisition unit acquires a target brain image Bt as a diagnostic target and a plurality of past brain images Bpi, which have earlier imaging dates and times than the target brain image Bt, for the same subject. A similarity calculation unit calculates the similarity between each of the plurality of past brain images Bpi and a standard brain image Bs. A selection unit selects a reference brain image B0 serving as a reference for calculating the amount of change of the brain from the plurality of past brain images Bpi.

A method includes receiving a time series of slice images of medical imaging. The images have a region of interest located at a lung lesion. The method also includes tracking over at least one subset of slice images in a time series of slice images variations over time of at least one image parameter at the set of points in the region of interest. Classifier processing is applied to set of signals indicative of tracked time variations of the at least one image parameter at respective points in the set of points. A classification signal is indicative of the tracked time variations of the at least one image parameter reaching or failing to reach at least one classification threshold.

A method of ultrasound imaging that includes acquiring ultrasound data, and acquiring a target object quality parameter for a target object during the process of acquiring the ultrasound data. One or more processors determine a target object quality level for the target object based on the target object quality parameter and automatically selects a target object quality indicator based on the target object quality level. The one or more processors also generate an image based on the ultrasound data and including the target object quality indicator associated with the target object, and displays the image on a display device.

A method of ultrasound imaging that includes acquiring ultrasound data, and acquiring a target object quality parameter for a target object during the process of acquiring the ultrasound data. One or more processors determine a target object quality level for the target object based on the target object quality parameter and automatically selects a target object quality indicator based on the target object quality level. The one or more processors also generate an image based on the ultrasound data and including the target object quality indicator associated with the target object, and displays the image on a display device.

The present invention discloses a method for detecting skin conditions, and the method includes the steps of: capturing a skin image from a suspected subject; decomposing the skin image into an RBX image through RBX color-space transformation; and determining skin condition of the subject according to a parameter of a color model of the RBX image.

Medical imaging study summary engine mechanisms are provided. The mechanisms receive a medical imaging study having data representing a plurality of medical images of a patient. The mechanisms generate a temporal trajectory data structure of at least a subset of the medical images in the plurality of medical images, wherein the temporal trajectory data structure specifies topological changes in temporally subsequent medical images in the plurality of medical images. The mechanisms select medical image data corresponding to selected medical images from the medical imaging study data structure based on the temporal trajectory data structure. The mechanisms output the selected medical image data via a medical imaging study user interface.

A method for processing images of lungs, the method comprising defining an inhale region of interest of the lungs at an inhale position and an exhale region of interest of the lungs at an exhale position, determining a spatial transformation of each voxel within the lungs between the lungs at the inhale position and the lungs at the exhale position to provide displacement vector estimates for each voxel within the lungs, and performing volume change inference operations to determine a volume change between the lungs at the inhale position and the lungs at the exhale position based on the inhale region of interest, the exhale region of interest, and the displacement vector estimates for each voxel within the lungs.

The disclosure provides a theseometer or proprioceptometer for objectively quantifying the proprioceptive performance of a subject such as a human. The disclosed theseometer is a device comprising a clear, rigid material or screen having or exhibiting a distinguishable target embraced by a series of concentric rings, a digital camera with a lens concentric to the target, a base unit comprising an electronic processor and memory for analyzing data and, optionally, a wheeled base to provide mobility and portability.

An image display apparatus includes an image obtainer, a hardware processor, and a display. The image obtainer obtains a plurality of medical images of a same target region taken through serial radiography along a time axis. The hardware processor generates a display image based on the medical images obtained by the image obtainer. The display displays the display image generated by the hardware processor. The hardware processor combines the medical images into one composite medical image as the display image.