Some embodiments are directed to a segmentation of medical images. For example, a medical image may be registering to multiple atlas images after which a segmentation function may be applied. Multiple segmentation may be fused into a final overall segmentation. The atlas images may be selected on the basis of high segmentation quality or low registration quality.

The present disclosure relates to systems, devices, and methods to augment a two-dimensional image.

A segmentation method for tumor regions in a pathological image of clear cell renal cell carcinoma based on deep learning includes data acquisition and pre-processing, building and training of a classification network SENet and prediction of tumor regions. The present invention studies clear cell renal cell carcinoma based on pathological images, yielding results with higher reliability than judgments made based on CT or MRI images. The present invention overcomes the drawback that the previous research on clear cell renal cell carcinoma is only limited to judgment on presence by being able to visually provide the position and size of tumor regions, which is convenient for the medical profession to better study the pathogenesis and directions to the treatment of clear cell renal cell carcinoma.

An interactive image marking method is introduced. The interactive image marking method includes the following steps, displaying a target image and at least one marked region in the target image; receiving an interactive signal, where the interactive signal corresponds to a first pixel of the target image; calculating a correlation between the first pixel and pixels of the target image, and determining a correlation range in the target image according to the correlation; editing the marked region according to the correlate range; and displaying the edited marked region. In addition, an electronic device and a recording medium using the method are also introduced.

Systems and methods for processing electronic images from a medical device comprise receiving an image frame from the medical device, and determining a first color channel and a second color channel in the image frame. A location of an electromagnetic beam halo may be identified by comparing the first color channel and second color channel. Edges of an electromagnetic beam may be determined based on the electromagnetic beam halo, and size metrics of the electromagnetic beam may be determined based on the edges of the electromagnetic beam. A visual indicator on the image frame may be displayed based on the size metrics of the electromagnetic beam.

An image segmentation apparatus for magnetic resonance imaging according to an embodiment includes processing circuitry. The processing circuitry is configured to obtain a localizer image of an organ, the localizer image being three-dimensional or being in a plurality of layers and two-dimensional. The processing circuitry is configured to temporarily localize, on a basis of the localizer image, a segment in which the organ is present in terms of the layer direction of a plurality of slices included in the localizer image. The processing circuitry is configured to obtain a segmentation result of the organ, by performing an image segmentation process on the localizer image positioned inside the segment in which the organ is present.

Systems and methods for processing electronic images from a medical device comprise receiving an image frame from the medical device, and determining a first color channel and a second color channel in the image frame. A location of an electromagnetic beam halo may be identified by comparing the first color channel and second color channel. Edges of an electromagnetic beam may be determined based on the electromagnetic beam halo, and size metrics of the electromagnetic beam may be determined based on the edges of the electromagnetic beam. A visual indicator on the image frame may be displayed based on the size metrics of the electromagnetic beam.

Provided are a medical image displaying apparatus and a medical image displaying method for registering an ultrasound image with a previously obtained medical image and outputting a result of the registration, the medical image displaying method including: transmitting ultrasound signals to an object and receiving ultrasound echo signals from the object via an ultrasound probe of the medical image displaying apparatus; obtaining a first ultrasound image based on the ultrasound echo signals; performing image registration between the first ultrasound image and a first medical image that is previously obtained; obtaining a second ultrasound image of the object via the ultrasound probe; obtaining a second medical image by transforming the first medical image to correspond to the second ultrasound image; and displaying the second medical image together with the second ultrasound image.

A renal function assessment method includes following steps. A target kidney ultrasound image data of a subject is provided. An image pre-processing step is performed, wherein an image size of the target kidney ultrasound image data is adjusted, and the target kidney ultrasound image data is normalized according to an average and a standard deviation of a visual image database to obtain an after-processed target kidney ultrasound image data. A feature extracting step is performed, wherein the after-processed target kidney ultrasound image data is trained to achieve a convergence by a first deep-learning classifier to obtain an image feature of the after-processed target kidney ultrasound image data. A determining step is performed, wherein the image feature of the after-processed target kidney ultrasound image data is analyzed by the first deep-learning classifier to obtain an assessing result of an estimated glomerular filtration rate (eGFR).

Disclosed herein is a stone removing apparatus and a stone size measuring method, which can take a picture of a stone and measure the size of the stone in order to stably remove the stone without damaging a human body. The stone removing apparatus includes: an insertion tube having an inner space; a guide tube inserted into the inner space of the insertion tube to be moved; a wire inserted into the guide tube to be movable; a basket disposed at the front of the wire to grasp a stone; an imaging unit disposed at the front end of the guide tube in order to take an image of a stone grasped by the basket; and a control unit electrically connected with the imaging part to analyze the image taken by the imaging unit, wherein the control unit calculates a distance between the imaging unit and the basket to measure the actual size of the stone using the calculated distance.