Abstract: The present application discloses a method, device, and system for processing a medical image. The method includes obtaining, by one or more processors, a first medical image, wherein the first medical image includes a representation of a target organ, and processing, by the one or more processors, the first medical image based at least in part on a first machine learning model. A classification result associated with the first medical image and a first image of a target region in the first medical image are obtained based at least in part on the processing of the first medical image using the first machine learning model.

Abstract: A method and a system for detecting pesticide residues in tea based on a surface-enhanced Raman scattering (SERS) sensor are provided. An octahedral gold-silver hollow cage-based sensor is prepared, mixed with a pesticide standard solution and analyzed to obtain SERS spectral data. The SERS spectral data is processed, and a quantitative model is established based on the processed SERS spectral data. Based on the quantitative model, the detection of thiram and pymetrozine in tea samples can be completed. By means of an octahedral cuprous oxide template, gold-silver octahedral hollow cage (Au—AgOHCs) nanomaterials are prepared by reduction of gold and silver ions and removal of the template by acid dissolution, so as to prepare the SERS sensor, which can be applied to the rapid and quantitative detection of thiram and pymetrozine in tea samples.

Abstract: A method and a system for detecting pesticide residues in tea based on a surface-enhanced Raman scattering (SERS) sensor are provided. An octahedral gold-silver hollow cage-based sensor is prepared, mixed with a pesticide standard solution and analyzed to obtain SERS spectral data. The SERS spectral data is processed, and a quantitative model is established based on the processed SERS spectral data. Based on the quantitative model, the detection of thiram and pymetrozine in tea samples can be completed. By means of an octahedral cuprous oxide template, gold-silver octahedral hollow cage (Au—AgOHCs) nanomaterials are prepared by reduction of gold and silver ions and removal of the template by acid dissolution, so as to prepare the SERS sensor, which can be applied to the rapid and quantitative detection of thiram and pymetrozine in tea samples.

Abstract: The present application discloses a method, device, and system for processing a medical image. The method includes obtaining, by one or more processors, a target image, segmenting, by the one or more processors, a target region image from the target image, wherein the target region image comprises a target object region in the target image, analyzing, by the one or more processors, the target region image based at least in part on a machine learning model, and obtaining by the one or more processors, a recognition result based at least in part on the analysis of the target region image.

Abstract: An image recognition method includes: obtaining an image; extracting a target image region corresponding to a target part from the image, wherein the target image region includes a target object; determining a location of the target object in the target image region (i) according to pixel values of pixels in the target image region and a location relationship between the pixels, or (ii) inputting the target image region to a trained segmentation model to obtain the location of the target object in the target image region; and displaying a recognition result of the image, wherein the recognition result indicates the location of the target object in the target image region.

Abstract: Segmenting an image is disclosed including acquiring a first image and a second image, the first image and the second image being obtained based on a same imaging target, and a resolution of the first image being greater than a resolution of the second image, performing image segmentation processing based on a plurality of sub-images of the first image to obtain a first initial segmentation result, performing image segmentation processing based on the second image to obtain a second initial segmentation result, merging, based on the imaging target, the first initial segmentation result with the second initial segmentation result to obtain a target segmentation result, and outputting or storing the target segment result.

Abstract: An ultrasound diagnostic apparatus includes processing circuitry. The processing circuitry generates a first image based on an echo signal obtained by transmission and reception of ultrasound waves. The processing circuitry acquires a second image that is an image generated by a medical image diagnostic apparatus. The processing circuitry performs a registration of the first image and the second image, by discretely setting a plurality of relative positions of the first image and the second image within a specified range, calculating the similarity between the first image and the second image corresponding to the plurality of relative positions respectively, updating the plurality of the relative positions based on the calculation result of the similarity, and recalculating the similarity corresponding to the plurality of the updated relative positions respectively. The processing circuitry causes a display to display the images obtained after the registration.

Abstract: A medical image diagnostic apparatus according to an embodiment includes processing circuitry. The medical image diagnostic apparatus performs image registration between medical image data. The processing circuitry extracts a structure of the subject included in the medical image data. The processing circuitry sets a display scale of the subject to a specified value. The processing circuitry performs image registration between the medical image data on the display scale of the specified value.

Abstract: An analysis apparatus according to an embodiment includes processing circuitry. The processing circuitry performs registration between first ultrasound image data obtained at a first phase by an ultrasound diagnostic apparatus and first medical image data obtained by a medical image diagnostic apparatus other than the ultrasound diagnostic apparatus and performs registration between the first ultrasound image data and second ultrasound image data obtained at a second phase different from the first phase by the ultrasound diagnostic apparatus, to generate second medical image data registered with the second ultrasound image data; and combines the second ultrasound image data and the second medical image data to generate a single image, thereby performing registration between ultrasound image data by the ultrasound diagnostic apparatus and medical image data by the medical image diagnostic apparatus.

Abstract: An image recognition method includes: obtaining an image; extracting a target image region corresponding to a target part from the image, wherein the target image region includes a target object; determining a location of the target object in the target image region (i) according to pixel values of pixels in the target image region and a location relationship between the pixels, or (ii) inputting the target image region to a trained segmentation model to obtain the location of the target object in the target image region; and displaying a recognition result of the image, wherein the recognition result indicates the location of the target object in the target image region.

Abstract: A medical image diagnostic apparatus according to an embodiment includes processing circuitry configured to determine a plurality of small blocks for each of a plurality of pieces of medical image data, generate a plurality of superpixels corresponding to the plurality of small blocks, assign a label to at least one of the plurality of pieces of medical image data, and perform registration between the plurality of pieces of medical image data using the plurality of superpixels and the label.

Abstract: The present application discloses a method, device, and system for processing a medical image. The method includes obtaining, by one or more processors, a first medical image, wherein the first medical image includes a representation of a target organ, and processing, by the one or more processors, the first medical image based at least in part on a first machine learning model. A classification result associated with the first medical image and a first image of a target region in the first medical image are obtained based at least in part on the processing of the first medical image using the first machine learning model.

Abstract: The present application discloses a method, device, and system for processing a medical image. The method includes obtaining, by one or more processors, a target image, segmenting, by the one or more processors, a target region image from the target image, wherein the target region image comprises a target object region in the target image, analyzing, by the one or more processors, the target region image based at least in part on a machine learning model, and obtaining by the one or more processors, a recognition result based at least in part on the analysis of the target region image.

Abstract: Segmenting an image is disclosed including acquiring a first image and a second image, the first image and the second image being obtained based on a same imaging target, and a resolution of the first image being greater than a resolution of the second image, performing image segmentation processing based on a plurality of sub-images of the first image to obtain a first initial segmentation result, performing image segmentation processing based on the second image to obtain a second initial segmentation result, merging, based on the imaging target, the first initial segmentation result with the second initial segmentation result to obtain a target segmentation result, and outputting or storing the target segment result.

Abstract: An analysis apparatus according to an embodiment includes processing circuitry. The processing circuitry performs registration between first ultrasound image data obtained at a first phase by an ultrasound diagnostic apparatus and first medical image data obtained by a medical image diagnostic apparatus other than the ultrasound diagnostic apparatus and performs registration between the first ultrasound image data and second ultrasound image data obtained at a second phase different from the first phase by the ultrasound diagnostic apparatus, to generate second medical image data registered with the second ultrasound image data; and combines the second ultrasound image data and the second medical image data to generate a single image, thereby performing registration between ultrasound image data by the ultrasound diagnostic apparatus and medical image data by the medical image diagnostic apparatus.

Abstract: A medical image diagnostic apparatus according to an embodiment includes processing circuitry. The medical image diagnostic apparatus performs image registration between medical image data. The processing circuitry extracts a structure of the subject included in the medical image data. The processing circuitry sets a display scale of the subject to a specified value. The processing circuitry performs image registration between the medical image data on the display scale of the specified value.

Abstract: An ultrasound diagnostic apparatus includes processing circuitry. The processing circuitry generates a first image based on an echo signal obtained by transmission and reception of ultrasound waves. The processing circuitry acquires a second image that is an image generated by a medical image diagnostic apparatus. The processing circuitry performs a registration of the first image and the second image, by discretely setting a plurality of relative positions of the first image and the second image within a specified range, calculating the similarity between the first image and the second image corresponding to the plurality of relative positions respectively, updating the plurality of the relative positions based on the calculation result of the similarity, and recalculating the similarity corresponding to the plurality of the updated relative positions respectively. The processing circuitry causes a display to display the images obtained after the registration.

Abstract: A medical image diagnostic apparatus according to an embodiment includes processing circuitry configured to determine a plurality of small blocks for each of a plurality of pieces of medical image data, generate a plurality of superpixels corresponding to the plurality of small blocks, assign a label to at least one of the plurality of pieces of medical image data, and perform registration between the plurality of pieces of medical image data using the plurality of superpixels and the label.

Abstract: An ultrasound diagnosis apparatus according to an embodiment includes processing circuitry. The processing circuitry acquires a plurality of frames representing ultrasound images starting with an initial frame in time series. The processing circuitry compares a current frame and a previous frame to the current frame for determining the similarity therebetween, and generates a reference frame based on weighting processing on the initial frame and the previous frame using results of the comparison. The processing circuitry implements tracking processing between the reference frame and the current frame.

Abstract: An ultrasound diagnosis apparatus according to an embodiment includes processing circuitry. The processing circuitry acquires a plurality of frames representing ultrasound images starting with an initial frame in time series. The processing circuitry compares a current frame and a previous frame to the current frame for determining the similarity therebetween, and generates a reference frame based on weighting processing on the initial frame and the previous frame using results of the comparison. The processing circuitry implements tracking processing between the reference frame and the current frame.