The brain appears to have organized cardiac frequency angiographic phenomena with such coherence as to qualify as vascular pulse waves. Separate arterial and venous vascular pulse waves may be resolved. This disclosure states the method of extracting a spatiotemporal reconstruction of the cardiac frequency phenomena present in an angiogram obtained at faster than cardiac frequency. A wavelet transform is applied to each of the pixel-wise time signals of the angiogram. If there is motion alias then instead a high frequency resolution wavelet transform of the overall angiographic time intensity curve is cross-correlated to high temporal resolution wavelet transforms of the pixel-wise time signals. The result is filtered for cardiac wavelet scale then pixel-wise inverse wavelet transformed. This gives a complex-valued spatiotemporal grid of cardiac frequency angiographic phenomena. It may be rendered with a brightness-hue color model or subjected to further analysis.

The present invention relates to deep learning for automated assessment of malignancy of lesions. According to a first aspect, there is provided a computer-aided method of malignancy assessment of lesions, the method comprising the steps of: receiving input data; performing a first analysis on the input data to identify one or more lesions, generating a probability map for the one or more lesions from the input data; performing a second analysis on the input data to obtain a malignancy probability mask for the input data; and generating an overlay for the input data by combining the lesion probability map with the malignancy probability mask.

A computer-implemented method for obtaining thermal image data of a body part and a thermal imager are disclosed. The method comprises receiving image data of a body part, the image data including thermal image data, the thermal image data including thermal image data of the body part and background thermal image data, applying a classifier to the image data to detect a profile of the body part, the classifier being configured to use image data other than the thermal image data to perform the detection, generating a mask from said profile, and applying the mask to the thermal image data to remove the background thermal image data and obtain thermal image data of the body part.

A portable, rechargeable lateral flow test strip immunoassay in vitro diagnostic device includes a color imaging sensor for imaging a lateral flow test strip, a lens that images a substantial part of the 2D surface of the lateral flow test strip onto the color imaging sensor and image processing software that identifies patterns in the test lines and/or dots or other distributions in the test strip and compensates for distortions, non-uniformities or anomalies in the lines and/or dots or other distributions in the test strip.

[Object] To more precisely determine an event regarding a biological sample. [Solution] An information processing device according to the present technology includes: a first information acquisition section that acquires first information on the basis of a still image in a frame corresponding to a predetermined time point, from among a plurality of images of a biological sample captured in a time-series manner; a second information acquisition section that acquires second information on the basis of an interframe change of the plurality of images in a predetermined period; and a determination section that determines an event regarding the biological sample, using the first information and the second information.

Systems, devices, and methods for automated, fast lung pulse detection are provided. In an embodiment, a system for detecting pneumothorax (PTX) includes an ultrasound probe in communication with a processor. The processor is configured to generate, using the ultrasound imaging data received from the ultrasound probe, an M-mode image including a pleural line of the lung. Using the M-mode image, the processor generates a difference image comprising a plurality of difference lines generated by subtracting adjacent samples of the M-mode image. The processor analyzes the difference image to determine whether the difference image includes a periodic signal corresponding to the heartbeat of the patient and outputs a graphical representation of detecting the lung pulse based on determining that the difference image includes the periodic signal corresponding to the heartbeat.

A computer-implemented method, computer program product and computer system for human gait analysis are described. A video stream of an individual walking includes a plurality of frames reflecting the walk of the individual. A skeletal motion of the individual is extracted, by inferring, from the obtained video stream, three-dimensional gait information. The three-dimensional gait information includes estimates of the individual's joint locations including at least the individual's foot locations on each frame, wherein the estimates are derived by matching for each frame two-dimensional coordinates of the respective frame with respective three-dimensional model information of the individual's body. One or more gait parameters of the individual may be determined, based on the individual's foot locations in local extrema frames showing local extrema of the distance between one foot location of the individual and a corresponding reference joint location.

A method of assessing a feature on a patient's skin surface includes capturing (i) an image of the patient's skin surface with a camera of a portable capture device and (ii) range information with an auxiliary range measurement device that is attached to the portable capture device. Based on the range information, a single range value can be determined between the capture device and the patient's skin surface. In some embodiments, a scale can be associated with the image based on the single range value.

A computer-implemented method for tracking surgical textiles includes receiving a first image comprising a first textile-depicting image region, receiving a second image comprising a second textile-depicting image region, measuring a likelihood that the first and second image regions depict at least a portion of the same textile, and incrementing an index counter if the measure of likelihood does not meet a predetermined threshold. The measure of likelihood may be based on at least one classification feature at least partially based on aspects or other features of the first and second images.

An image diagnosis apparatus (10) performs a diagnosis assistance process using images (moving image) generated by an endoscope or the like. The image diagnosis apparatus (10) includes a first processing unit (110) and a second processing unit (120). The first processing unit (110) executes preprocessing of deciding whether or not a tumor judgment process is necessary with respect to each of a plurality of input images. The second processing unit (120) performs the tumor judgment process with respect to the input image for which it is decided that “the tumor judgment process is necessary” in the preprocessing executed by the first processing unit (110).