A method for medical imaging may include obtaining a plurality of successive images of a region of interest (ROI) including at least a portion of an object's heart. The plurality of successive images may be based on imaging data acquired from the ROI by a scanner without electrocardiography (ECG) gating. The plurality of successive images may be related to one or more cardiac cycles of the object's heart. The method may also include automatically determining, in the plurality of successive images, target images that correspond to at least one of the one or more cardiac cycles of the object's heart.

Provided are ex vivo systems and methods of predicting the response of a drug or other agent on a tissue. In some embodiments, the systems and methods comprise cutting a tissue into tissue fragments, adding a drug or other agent to the tissue fragments based on an estimated tumor content, and performing an ex vivo measurement on the tissue fragments.

Device and Method for Evaluating Dark Field Images The present invention relates to the use of dark field X-ray images in an ablation treatment of a tumour. By acquiring dark field X-ray images displaying the region of interest targeted in the ablation treatment, information can be derived which allows taking a decision on terminating the ablation treatment. A set of dark field X-ray images is received (101), which is acquired at different time instants and comprises the region of interest. Dark field X-ray images of the set are compared (102), for example by determining difference images between the individual images. If during that comparison a change in the dark field X-ray images is detected over time in the region of interest, then a signal is generated (103) indicating a change has occurred. That signal may indicate that healthy tissue is being affected instead of the tumour and that consequently the ablation treatment should be ended.

A method, an apparatus and a system for conveniently measuring coronary artery vascular evaluation parameters are provided by the disclosure. The measurement method includes: measuring a pressure P.sub.d at a distal end of coronary artery stenosis and/or a pressure P.sub.a at a coronary artery inlet via a pressure guide wire (S100); performing coronary angiography for a blood vessel to be measured (S200); selecting an angiogram image of a first body position and an angiogram image of a second body position of the blood vessel to be measured (S300); selecting a segment of blood vessel from a proximal end to a distal end of the coronary artery for segmentation, and obtaining a three-dimensional coronary artery vascular model by three-dimensional modeling (S400); injecting a contrast agent, and obtaining an average time T.sub.a taken for the contrast agent passing from an inlet to an outlet of the segment of blood vessel (S500); obtaining a time T.sub.max taken for the contrast agent passing from the inlet to the outlet of the segment of blood vessel in a maximum dilated state according to hydrodynamic formulas (S600); obtaining coronary artery vascular evaluation parameters (S700).

A crop yield prediction program includes: a degree-of-association acquisition step of acquiring in advance a degree of association between a combination of reference image information which is a captured image of a growing crop and reference soil information about a soil in which the crop is planted and a yield of the growing crop as harvested for the combination, the degree of association being represented in three or more levels; an information acquisition step of, when making a new prediction of the yield of the crop, capturing an image of a new growing crop to acquire image information and to acquire soil information about a soil in which the crop is planted; and a prediction step of predicting a yield of the new growing crop with reference to the degree of association acquired at the degree-of-association acquisition step and based on the image information and the soil information.

System and method for evaluating the vascular health condition of a subject using thermal imaging is disclosed. The system and method includes capturing passive thermal images and/or videos of at least one body part, detecting a predefined region of the body part in each frame of the captured images/videos, and segmenting one or more portions from the detected predefined region in each frame of the captured images/videos. Further a region of interest comprising blood vessels in the segmented portions in each frame of the captured images/videos is identified to extract pixel values from each frame of the captured images/videos representing biosignals. Parameters associated with the potential biomarkers of vascular functions and hemodynamics of the subject are determined based on the extracted pixel values representing biosignals. The vascular health condition of the subject is evaluated based on deviation of the determined parameters with respect to predetermined reference parameters.

Method for detecting or predicting the occurrence of a cell event, selected from between cell division or cell death, in a sample (10), the sample extending in at least one sample plane (P.sub.10) and comprising cells (10.sub.p) immersed in a medium, the method comprising the following steps: a) arranging the sample between a light source (11) and an image sensor (16); b) illuminating the sample (10) using the light source (11) and acquiring a plurality of successive images ((I.sub.i(t.sub.i), I.sub.1(t.sub.i+1) . . . I.sub.1(t.sub.i+K)) of the sample at different instants ([t.sub.i; t.sub.i+K]) forming an acquisition time range, each image being representative of an exposure light wave to which the image sensor is exposed; c) on the basis of each acquired image of the sample, calculating an observation image at each instant (I.sub.10(t.sub.i), I.sub.10(t.sub.i+1) . . . I.sub.10(t.sub.i+K)), the observation image corresponding to a spatial distribution of an optical path difference induced by the cells, or of an absorbance of the cells, in the sample plane (P.sub.10); d) using the observation images resulting from c) as input data of a supervised artificial intelligence algorithm (CNN.sub.d, CNN.sub.p), so as to predict or locate an occurrence of the cell event.

A method according to one embodiment of the present disclosure comprises receiving a first image of a patient's anatomy, the first image generated at a first time and depicting a plurality of rigid elements; receiving a second image of the patient's anatomy, the second image generated at a second time after the first time and depicting the plurality of rigid elements; determining a transformation from the first image to the second image for each one of the plurality of rigid elements to yield a set of transformations; calculating a homography for each transformation in the set of transformations to yield a set of homographies; and identifying, using the set of homographies, a common portion of each transformation attributable to a change in camera pose, and an individual portion of each transformation attributable to a change in rigid element pose.

Methods and apparatuses for assessing oral health and automatically providing diagnosis of one or more oral diseases. Described herein are intraoral scanning methods and apparatuses for collecting and analyzing image data and to detect and visualize features within image data that are indicative of oral diseases or conditions, such as gingival inflammation or oral cancer. These methods and apparatuses may be used for identifying and evaluating lesions, redness and inflammation in soft tissue and caries and cracks in the teeth. The methods an include training a machine learning model and using the trained machine learning model to provide a diagnosis of an oral disease or condition based on image data collected using multiple scanning modes of an intraoral scanner.

The present invention relates to the field of medical imaging in the absence of contrast agents. In one form, the invention relates to the field of imaging vessels, particularly blood vessels such as the pulmonary vasculature and is suitable for use as a technique for detecting pulmonary embolism (PE), such as acute PE. Embodiments of the present invention provide improved image processing techniques having the capability to extract and use image data to overcome the need for contrast agents to distinguish between different types of tissue. Furthermore, it has also been realised that the image data accessed by the improved image processing can be used to identify irregularities in vessels.