University System of Maryland

Richwave Technology Corp.

Wei-min Liu

Hsiang-Feng Chi

Khan Mohammad Siddiqui

Chein-I Chang

Han-Jieh Chang

Po-Fu Wan

Nabile Safdar

Bharath Ramakrishna

Eliot Siegel

An object recognition method includes generating Doppler spectrogram data according to an echo signal, the echo signal being relating to an object; transforming N sets of time-domain data of the Doppler spectrogram data corresponding to N velocities into N sets of cadence spectrogram data, respectively; combining the N sets of spectrogram data to obtain 1D/2D cadence spectrum data, and acquiring a series of cadence feature from the 1D/2D cadence spectrum data to recognize the object.

Object recognition method and object recognition device

Techniques for automatically detecting meniscus include receiving pixels from a scanning device directed to a knee of a subject. Also received is a region of interest that includes pixels that correspond to at least a portion of a meniscus of the knee. Without human intervention, a meniscus extraction threshold is determined based on pixel intensities in the region of interest. A meniscus object portion of the scan data is further determined without human intervention based on the meniscus extraction threshold and a geometrical constraint. Other techniques for automatically detecting meniscal tears includes receiving a meniscus object portion of scan data from a scanning device and receiving threshold data that indicates a meniscus extraction threshold. Without human intervention, a propensity for meniscal tears is determined based on the threshold data and the meniscus object portion of the scan data.

Detecting meniscal tears in non-invasive scans

Growing community of inventors

Taipei, Taiwan

Wei-min Liu