A method and device are for automatic determination of the change of a hollow organ. The method includes providing a first medical image of the organ recorded at a first time; computing a first representation of the organ in the first image; computing a first reference-line of the organ based on the first representation and providing a second medical image of the organ recorded at a second point. The method further includes computing a second representation of the organ in the second image; computing a second reference-line of the organ based on the second representation of the organ; registering of the first and second reference-line to obtain at least one of matched representations of the organ and features derived from the matched representations of the organs; and comparing at least one of the matched representations of the organs and the features derived from the matched representations of the organ.

The present disclosure provides monitoring system, device and computed-implemented method for monitoring pressure ulcers. The monitoring system and the device are configured to: capture at least one image corresponding to a user; retrieve the anamnesis data of the user; and determine a pressure ulcers condition result corresponding to the at least one image and the anamnesis data according a pressure ulcers prediction model.

Systems and methods for detecting aortic aneurysms using ensemble based deep learning techniques that utilize numerous computed tomography (CT) scans collected from numerous de-identified patients in a database. The system includes software that automates the analysis of a series of CT scans as input (in DICOM file format) and provides output in two dimensions: (1) ranking CT scans by risks of adverse events from aortic aneurysm, (2) providing aortic aneurysm size estimates. A repository of CT scans may be used for training of deep neural networks and additional data may be drawn from localized patient information from institutions and hospitals which grant permission.

A method for determining healing progress of a tissue disease state includes receiving a thermal image of a target wound area from a thermal imaging system, processing the thermal image to construct an isotherm map of at least one selected area, determining a thermal index value from the isotherm map, correlating the wound thermal index value with a reference thermal index value representative of an injury-free state.

Provided are a leukocyte detection method, a system, an electronic device and a computer readable medium. The method comprises: acquiring a microcirculation image (S1); determining a location of an intra-tubular space of a capillary vessel from the microcirculation image (S2); and determining a leukocyte index based on image information of the intra-tubular space of the capillary vessel (S3).

The present disclosure relates to a method of determining a prognostic outlook for patients having metastatic breast cancer. The method includes receiving imaging data from an image of a patient that is receiving or that is to receive cycline dependent kinase 4 and 6 (CDK 4/6) inhibitor therapy for hormone receptor-positive (HR+) metastatic breast cancer. Radiomic heterogeneity features are extracted from imaging data associated with a metastasis within the imaging. A prognostic marker is determined from the radiomic heterogeneity features. The prognostic marker is indicative of a response of the patient to CDK 4/6 inhibitor therapy for HR+ metastatic breast cancer.

Various embodiments of the present disclosure are directed towards a method for predicting a response to treatment of small cell lung cancer (SCLC). The method includes generating a radiomic risk score (RRS) for the patient based on a plurality of radiomic features, wherein the RRS is prognostic of overall survival (OS) of the patient. The RRS is provided to a machine learning classifier that is trained to predict a response of the patient to a SCLC chemotherapy treatment based, at least in part, on the RRS. The machine learning classifier provides a classification of the patient into either a responder group (RG) or a non-responder group (NRG), where the NRG indicates the patient will not respond to the SCLC chemotherapy treatment and the RG indicates that the patient will respond to the SCLC chemotherapy treatment.

Cerebrospinal fluid (CSF) drainage systems. A system includes a conduit having a proximal end and a distal end. The conduit receives the CSF from a patient from the proximal end. The system includes a collection chamber coupled to the distal end. The collection chamber collects the CSF. The system includes a valve positioned on the conduit. The valve controls CSF flow into the collection chamber. The system includes a camera that captures an image of the CSF within the collection chamber. The system includes a processor coupled to the camera. The processor measures a flow rate of the CSF based on the image and controls the first valve to open for a first predetermined period and close for a second predetermined period until a determination of a predetermined amount of the CSF being drained from the patient is made by the processor based on the flow rate.

A risk evaluation system is provided with an imager and a controller. The imager takes images at different times of equipment having zones that do not overlap each other, and outputs the images that are taken. The controller detects a contact count of a number of times a living body contacts each of the zones in accordance with the images, decides evaluation information about a contact infection risk in each of the zones in accordance with the contact count, and outputs the evaluation information.

Ultrasound imaging systems for automatically identifying and saving ultrasound images relevant to a needle injection procedure, and associated systems and methods, are described herein. For example, an ultrasound imaging system includes a transducer for transmitting/receiving ultrasound signals during a needle injection procedure, and receive circuitry configured to convert the received ultrasound signals into ultrasound image data. The image data can be stored in a buffer memory. A processor can analyze the image data stored in the buffer memory to identify image data that depicts a specified injection event of the needle injection procedure, and the identified image data can be stored in a memory for archival purposes.