Alibaba Group Holding Limited

Toshiba Medical Systems Corporation

Canon Medical Systems Corporation

Alibaba (China) Co., Ltd.

Minfeng Xu

Yanhua Wang

Zhe Tang

Jianqiang Ma

Shuangrui Liu

Wenchao Guo

Qi Chen

Bing Han

Hong Yang

Shaobin Wang

Jianchun Zhao

Yang Zhang

Yanli Wang

Marco Razeto

Costas Plakas

Jianfeng Zhang

Jialin Zhang

Le Lyu

Heng Guo

Xiaotian Yang

A method for detecting a rib with a medical image, a device and a medium are provided. Feature coding is performed, by using a neural network model, on different rib regions in the medical image to obtain multiple feature vectors. According to a learned corresponding relationship between rib query items and the different rib regions, a feature vector for respective rib query item is determined. Parallel decoding is performed on the feature vector for respective rib query item to obtain a rib detection result corresponding to respective rib query item. The rib query items are endowed with semantic information in anatomy, such that respective rib query items may focus on features of different rib regions, and thus realizing controllable rib detection in instance-level. Any rib detection result includes a rib prediction classification and a prediction value of a pose parameter, in a three-dimensional space, of a rib detection box.

Method for detecting a rib with a medical image, device, and medium

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.

Medical image processing method and system and data processing method

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.

Data processing method, means and system

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.

Recognition method, apparatus, and device, and storage medium

A medical image processing apparatus according to an embodiment includes an estimation circuitry and a tracking circuitry. The estimation circuitry is configured to estimate the activity of the myocardium across a plurality of images at different time phases from a group of images where a plurality of images containing a myocardium are chronologically arranged. The tracking circuitry is configured to set a search range for tracking the myocardium in the group according to the activity of the myocardium and perform the tracking.

Medical image processing apparatus, medical image processing method and medical image device

A medical image processing apparatus according to an embodiment includes acquisition circuitry, extraction circuitry, calculation circuitry, and determination circuitry. The acquisition circuitry configured to acquire a first photographic image and a second photographic image that contain tree structures of a subject. The extraction circuitry configured to extract branch points of each of the tree structures in the first photographic image and the second photographic image. The calculation circuitry configured to calculate the similarities between the branch points in the first photographic image and the branch points in the second photographic image based on the feature quantities of the branch points. The determination circuitry configured to determine the corresponding path between the branch points in the first photographic image and the branch points in the second photographic image based on the similarities between the branch points calculated by the calculation circuitry.

Medical image processing apparatus and medical image processing method

A medical image processing apparatus according to one embodiment includes obtaining circuitry, calculating circuitry, and transforming circuitry. The obtaining circuitry takes an expiration time phase or an inspiration time phase as a benchmark time phase and obtains a benchmark line structure, which is a line structure of a bronchus in a lung field, from a medical image at the benchmark time phase. The calculating circuitry calculates a motion amount between a component depicted in the medical image at the benchmark time phase and a component depicted in a medical image at at least one other time phase than the benchmark time phase. The transforming circuitry transforms the benchmark line structure based on the motion amount to obtain an estimated line structure, which is estimated as a line structure at the at least one other time phase.

Growing community of inventors

Beijing, China

Minfeng Xu