The systems and method for processing scanning data of a scanning object are provided. The method may include acquiring, in a scanning process, at least two target phases of a motion of the scanning object, wherein the scanning process involves multiple data acquisition time points each of which corresponds to a scanning data set; identifying at least two first time periods during the scanning process, each first time period corresponding to one of the two target phases; determining a second time period that encloses the at least two first time periods; and retrieving once, from the multiple scanning data sets, second scanning data sets for reconstructing phase images each of which corresponds to one target phase, the second scanning data sets being acquired at second data acquisition time points of the multiple data acquisition time points within the second time period.

A kit for a fiducial marker-based registration of preinterventional image data to an intra-interventional scene is disclosed. The kit comprises: at least one first component, wherein the first component is configured for attachment to a body of a patient, wherein the first component comprises at least one base part of an arresting mechanism, at least one second component, wherein the second component comprises at least one fiducial which is localizable in the preinterventional image data, wherein the second component comprises at least one first counterpart of the arresting mechanism, at least one third component, wherein the third component comprises at least one mounting unit for mounting a spatially localizable tracking object on the third component, wherein the third component comprises at least one second counterpart of the arresting mechanism;
wherein the second component and the third component are selectively attachable to the first component by establishing a releasable mechanical connection between the base part and the first counterpart or between the base part and the second counterpart.

Apparatus and methods are described use with a bodily sample that contains cells. A microscope (24) is focused, such that a focal plane of the microscope (24) at least approximately coincides with a level at which at least some cells belonging to the sample are at least partially disposed. At least one on-focus microscopic image of the sample, while the focal plane of the microscope (24) approximately coincides with the level. The microscope (24) is focused such that the focal plane of the microscope is offset with respect to the level, at least one off-focus microscopic image of the sample is acquired, while the focal plane of the microscope (24) is offset with respect to the level. A property of at least a portion of the sample is determined, at least partially based upon the on-focus and off-focus images. Other applications are also described.

The present disclosure provides an image processing method, an image processing device, an electronic apparatus and a readable storage medium. The image processing method includes: obtaining feature map data of an input image; extracting a feature region in the feature map data in accordance with a size of a convolution kernel; performing windowing processing on the feature region; and obtaining a windowed feature map of the input image in accordance with the feature region obtained after the windowing processing.

An image processing method performed by a processor and including detecting positions of plural vortex veins in a fundus image of an examined eye, and computing a center of distribution of the plural detected vortex vein positions.

A system receives a first set of points corresponding to an anatomical feature. Each point in the first set of points represents a position in a first frame. The system receives a second set of points corresponding to the anatomical feature. Each point in the second set of points represents a position in a second frame. The system identifies a first subset of the first set of points and determines a first transformation to align the first subset of the first set of points with the second set of points. The first set of points is transformed based on the first transformation. The system identifies a second subset of the first set of points and determines a second transformation to align the first and second subsets of the first set of points with the second set of points. The first set of points are transformed based on the second transformation.

An image processing method to provide a final panoramic image of at least a portion of a head of a patient, wherein a plurality of different provisional panoramic images are calculated from captured frame data sets through the variation of a reconstruction parameter; the provisional panoramic images are scanned for recognizable structures; the imaging quality of the recognizable structures is determined; the variation of the at least one reconstruction parameter for the calculation of different provisional panoramic images of those frame data sets which have recognizable structures with the highest imaging quality is determined; and with reference to the determined variation of the reconstruction parameter of step a final panoramic image is calculated. A computer-readable storage medium comprising instructions which cause a computer to perform the method and an imaging system having such a storage medium are also described.

Systems and methods for reconstructing medical images are disclosed. Measurement data from positron emission tomography (PET) data, and measurement data from an anatomy modality, such as magnetic resonance (MR) data or computed tomography (CT) data, is received from an image scanning system. A PET image is generated based on the PET measurement data, and an anatomy image is generated based on the anatomy measurement data. A trained neural network is applied to the PET image and the anatomy image to generate an attenuation map. The neural network may be trained based on anatomy and PET images. In some examples, the trained neural network generates an initial attenuation map based on the anatomy image, registers the initial attenuation map to the PET image, and generates an enhanced attenuation map based on the registration. Further, a corrected image is reconstructed based on the generated attenuation map and the PET image.

A method involves use of multiple convolutional neural networks and multiple segmentation masks to programmatically generate a stool rating for a digital image of a diaper with stool. The method includes generating, by a first convolutional neural network, a first mask representing an identification of an area of the digital image that corresponds to stool, and a second mask representing an identification of an area of the digital image that corresponds to a diaper. The method further includes generating a third mask representing an intersection of the first and second masks, and generating a modified digital image utilizing the third mask. The method further includes determining, by a second convolutional neural network, a stool rating for the digital image of the diaper with stool by utilizing the modified digital image as input for the second convolutional neural network.

Provided are a capsule endoscope apparatus for supporting a lesion diagnosis and a lesion diagnosis supporting method using the same. The capsule endoscope apparatus for supporting lesion diagnosis includes an imaging unit configured to capture one or more images of an inside of a body, a control unit configured to detect a suspected lesion region in the images and perform a precision diagnosis procedure when a suspected lesion region corresponding to a value equal to or greater than a certain threshold is detected, an image processing unit configured to process the images in the precision diagnosis procedure, and a communication module configured to transmit and receive processed images to another capsule endoscope apparatus or a terminal by using a wireless communication method.