The disclosure relates to a system and method for image reconstruction. The method may include the steps of: obtaining raw data corresponding to radiation rays within a volume, determining a radiation ray passing a plurality of voxels, grouping the voxels into a plurality of subsets such that at least some subset of voxels are sequentially loaded into a memory, and performing a calculation relating to the sequentially loaded voxels. The radiation ray may be determined based on the raw data. The calculation may be performed by a plurality of processing threads in a parallel hardware architecture. A processing thread may correspond to a subset of voxels.

A method for obtaining a Fourier ptychography image using a smartphone comprises the steps of: (a) sequentially providing illumination of different angles to the sample by sequentially displaying, according to a first pattern composed of point light sources at different positions, the point light sources of the first pattern on a display of the smartphone; (b) obtaining an image for each illumination angle of the sample using a camera of the smartphone whenever illumination of different angles is provided by the point light sources of the first pattern; and (c) restoring a first Fourier ptychography image using a plurality of images for each illumination angle obtained using the camera of the smartphone.

A method for detecting the maximum potential presence of a material in an object. The method includes obtaining raw x-ray image data comprising a plurality of pixels for the object from an X-ray scanning device, wherein each pixel of the plurality of pixels has associated therewith an attenuation value and an effective atomic number (Z.sub.eff) for the pixel. The method further includes converting, for each pixel having a Z.sub.eff value greater than a threshold effective atomic number (Z.sub.eff-threshold), the Z.sub.eff at the pixel to the Z.sub.eff-threshold while applying a correction factor to the attenuation value for the pixel to bring the attenuation value into correspondence with the conversion of the Z.sub.eff value for the pixel and determining a maximum potential amount of the material present at each pixel based on the corrected attenuation value at the pixel. This renders material more apparent in visual display.

In a learning phase, a processor of a sample observation device: stores design data on a sample in a storage resource; creates a first learning image as a plurality of input images; creates a second learning image as a target image; and learns a model related to image quality conversion with the first and second learning images. In a sample observation phase, the processor obtains, as an observation image, a second captured image output by inputting a first captured image obtained by imaging the sample with an imaging device to the model. The processor creates at least one of the first and second learning images based on the design data.

The present disclosure relates to a medical observation system, an image processing method, and a program capable of providing image display more helpful for a surgeon. A correction processing unit performs correction processing on a wide-angle image which is a captured image of a medical treatment target, a clipping processing unit moves a clipping area for a display image clipped from the wide-angle image, and a correction control unit controls the correction processing according to a relative state of the clipping area to the wide-angle image. The present disclosure can be applied to, for example, an endoscopic surgery system.

Systems and methods for identifying a personalized prior within a generative model's latent vector space based on a set of images of a given subject. In some examples, the present technology may further include using the personalized prior to confine the inputs of a generative model to a latent vector space associated with the given subject, such that when the model is tasked with editing an image of the subject (e.g., to perform inpainting to fill in masked areas, improve resolution, or deblur the image), the subject's identifying features will be reflected in the images the model produces.

Systems and methods for training a restoration model can leverage training for two sub-tasks to train the restoration model to generate realistic and identity-preserved outputs. The systems and methods can balance the training of the generation task and the reconstruction task to ensure the generated outputs preserve the identity of the original subject while generating realistic outputs. The systems and methods can further leverage a feature quantization model and skip connections to improve the model output and overall training.

The present disclosure relates to a tag and a method, performed by the tag, of transmitting a response signal to a tag search signal. Specifically, the disclosed method of transmitting a response signal includes operations of receiving, from at least one of a plurality of slave nodes, the tag search signal including identification data for identifying the tag, charging an energy storage element in the tag by using the received tag search signal, obtaining the identification data for identifying the tag from the received tag search signal, determining whether the obtained identification data matches identification information previously stored in the tag, and outputting a response signal to the tag search signal when the energy storage element is charged greater than a predetermined value and the obtained identification data matches the identification information previously stored in the tag.

The disclosure provides an image processing device. An image processing device includes a neural network circuit, a gain control circuit, and an image merge circuit. The neural network circuit is configured to receive an input image, and perform an image processing operation on the input image according to fixed parameters to output a first intermediate image. The gain control circuit, coupled to the neural network circuit, is configured to receive the first intermediate image from the neural network circuit, and multiply the first intermediate image by at least one amplitude gain to output a second intermediate image. The image merge circuit, coupled to the gain control circuit, configured to receive the second intermediate image and the input image, and combine the second intermediate image and the input image to obtain an output image. In addition, a method for image enhancement is also provided.

A data processing method includes: receiving, through a display interface, first image data in an RGB format sent by a data transmit terminal, where the first image data is image data obtained after image blending is performed on ARGB data of a target image and image data of a preset background image, and the display interface is used to receive data in an RGB format; and performing data restoration processing on the first image data to obtain the ARGB data of the target image.