Methods and systems for analyzing a field. The methods and systems acquire a thermal image indicative of thermal energy emitted by the soil and/or plants in the field and process the thermal image to assess variations in certain characteristics of the soil and/or plants.

An imaging system and method for microbial growth detection, counting or identification. One colony may be contrasted in an image that is not optimal for another type of colony. The system and method provides contrast from all available material through space (spatial differences), time (differences appearing over time for a given capture condition) and color space transformation using image input information over time to assess whether microbial growth has occurred for a given sample.

An information processing system includes a first acquisition unit, a second acquisition unit, a movement control unit, and a state evaluation unit. The first acquisition unit acquires, from a first imaging unit, image data relating to a first image of a head of a subject that is captured at a first angle of view. The second acquisition unit acquires, from a second imaging unit, image data relating to a second image of an eye region of the subject that is captured at a second angle of view narrower than the first angle of view. The movement control unit moves a visual field range of the second imaging unit. The state evaluation unit evaluates a change in state of the eye of the subject.

Systems and methods for the image-based determination of the fluid status of a patient are described. In one example, an apparatus may include at least one processor and a memory coupled to the at least one processor. The memory may include instructions that, when executed by the at least one processor, may cause the at least one processor to receive an image that may include at least one image of a portion of a patient, determine fluid status information for the patient by processing the image via a trained computational model, the trained computational model trained based on at least one training image of the patient and a corresponding physical measurement of fluid status, the fluid status information indicating a current fluid status of the patient, and determine a treatment recommendation for the patient based on the fluid status information. Other embodiments are described.

Many biologic processes taking place inside a living organism are unpredictable in time and space, and cannot be known exactly. These mechanisms and interactions among them are better modeled as physiological random processes, the statistics of which are fully described by joint characteristic functionals. The present invention provides methods for the estimation of joint characteristic functionals through imaging of multiple physiological random processes. This technology can be used to study complex diseases, such as tumors and viral infections, by imaging the biological processes involved with disease progression and response to treatment.

Disclosed are a convex-linear bi-plane probe and its application method in prostate volume calculation. The present invention adopts the following technical solution: comprising a probe housing and a probe assembly contained in the probe housing, the probe assembly comprising a linear probe and a convex probe contained at the end of the linear probe, with the linear element inside the linear probe and the convex element inside the convex probe connected as one piece. The benefits of the present invention are that: by setting a convex probe at the end of the linear probe, and by connecting the linear element and the convex element as one, the volume of the probe can be significantly reduced. Furthermore, the use of convex-linear biplane probe and its integrated design collect two orthogonal ultrasound images of the prostate, which improves the accuracy of prostate volume calculation.

Systems and methods for predicting a patient response to various agents and/or combinations of agents using ex vivo dosing and imaging are disclosed. In one example, a method of forming a solid culture that includes isolating target cells from a patient sample, forming stained cells from the isolated cells by staining the isolated cells with a light-responsive dye; and encapsulating the stained cells in a hydrogel

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.

Methods and apparatuses for adjusting three-dimensional (3D) dental model data of a patient's dentition to detect and remove one or more attachments on a dental structure (e.g., tooth) of the patient's dentition by asynchronously allowing user to approve and/or modify the identified attachments. These methods may reduce the time required to generate accurate 3D dental models and therefore may reduce and streamline the process of generating dental treatment plans.

In an approach for classifying regions of tissue captured in multispectral videos into medically meaningful classes using GPU accelerated perfusion estimation, a processor receives one or more multispectral videos of a subject tissue of a patient. A processor extracts one or more fluorescence time series profiles from the one or more multispectral videos. A processor estimates one or more sets of perfusion parameters based on the one or more fluorescence time series profiles. A processor inputs one or more feature vectors into a classifier, wherein the one or more feature vectors are derived the one or more sets of perfusion parameters. A processor receives a classification result for each of the one or more feature vectors, wherein the classification result comprises a set of medically relevant labels for each of the one or more feature vectors with a level of certainty for each label of the set of medically relevant labels.