A visible-light-image physiological monitoring system with thermal detecting assistance is disclosed. The system takes a visible-light image and a thermal image of a body at the same time. A processing unit identifies a body feature of the visible-light image and determines a coordinate of the feature. In a learning mode, an initial temperature of the body feature is determined from the thermal image according to the coordinate of the body feature. After then, a physiological status monitoring mode is executed to monitor the temperature changes of the body feature and output an alarm when the temperature is determined to be abnormal. Therefore, a monitoring accuracy of the visible-light-image physiological monitoring system is increased and avoids transmitting false alarms or no alarms.

A dynamic image analysis apparatus includes a hardware processor and a display. The hardware processor performs tagging for classifying. The hardware processor extracts a feature amount from frame images and calculates a change amount in a time direction of the feature amount. When a second dynamic image is input, the hardware processor selects an extractable feature amount from a related dynamic image which is the first dynamic image determined to be related with the second dynamic image, the first dynamic image and the second dynamic image. The display is capable of displaying a change over time in the frame images included in one occasion of imaging of the dynamic image, the change over time between the second dynamic image and the selected related dynamic image and the change over time between the feature amount extracted from the second dynamic image and the feature amount extracted from the related image.

Systems and methods for tracking healing progress of multiple adjacent wounds are provided. In one embodiment, a system may include a processor configured to receive a first image of a plurality of adjacent wounds near a form of colorized surface having colored reference elements, determine colors of the plurality of wounds, correct for local illumination conditions, receive a second image of the plurality of wounds near the form of colorized surface, to determine second colors of the plurality of wounds in the second image, match each of the plurality of wounds in the second image to a wound of the plurality of wounds in the first image, and determine an indicator of the healing progress for each of the plurality of wounds based on changes between the first image and the second image.

From a plurality of medical images in time phases, a target site is extracted from at least one medical image, a reference point is set on each of a target-site side, and a periphery side of the target site which are on across from each other over an outline of the extracted target site, and movement information for the reference points is calculated.

One variation of a method for monitoring growth of plants within a facility includes: aggregating global ambient data recorded by a suite of fixed sensors, arranged proximal a grow area within the facility, at a first frequency during a grow period; extracting intermediate outcomes of a set of plants, occupying a module in the grow area, from module-level images recorded by a mover at a second frequency less than the first frequency while interfacing with the module during the period of time; dispatching the mover to autonomously deliver the module to a transfer station; extracting intermediate outcomes of the set of plants from plant-level images recorded by the transfer station while sequentially transferring plants out of the module at the conclusion of the grow period; and deriving relationships between ambient conditions, intermediate outcomes, and final outcomes from a corpus of plant records associated with plants grown in the facility.

Topological evolution of a lesion within a time series of medical imagery is provided. In various embodiments, a time series of medical images is read. Each of the images depicts a subject anatomy and a lesion. The lesion has a size and a contour within each of the medical images. At least one anatomical label is read for the subject anatomy within each of the plurality of images. Based upon the contour of the lesion within each of the medical images and based on the at least one anatomical label, a further contour of the lesion is predicted outside of the time series.

In a method for analyzing acquired magnetic resonance images, an image series is provided that includes acquired magnetic resonance images of a slice of an object, picture elements of the acquired magnetic resonance images of the image series are fitted to generate a parameter map and an error map, the acquired magnetic resonance images are automatically segmented to generate image segments, histograms of the parameter map and the error map are generated based on the image segments, and the histograms are analyzed to generate an output of analysis results and/or generate a visualization including the parameter map, the error map, and the image segments. The acquired magnetic resonance images can have a variation of a contrast-determining acquisition parameter.

A medical scan natural language analysis system is operable to generate a medical report natural language model based on a selected set of medical reports of the plurality of medical reports and the at least one medical code mapped to each of the selected set of medical reports. A medical report that is not included in the selected set is received via a network. A medical code is determined by utilizing the medical report natural language model on the first medical report. The medical code is mapped to a medical scan corresponding to the medical report.

A method for visualizing a tubular object from a set of volumetric data may include the steps of: determining a viewing direction for the tubular object; selecting a constraint subset of the tubular object within the volumetric data; defining a cut-surface through the volumetric data and including the constraint subset of the tubular object within the volumetric data; and rendering an image based upon the determined viewing direction and the volumetric data of the tubular object along the intersection of the volumetric data and the defined cut-surface. Additionally or alternatively, the method may identify a plurality of bifurcations in the tubular object; assign a weighting factor to each identified bifurcation; determine a bifurcation normal vector associated with each bifurcation; determine a weighted average of the bifurcation normal vectors; and render an image of the volumetric data from a perspective parallel to the weighted average of the bifurcation normal vectors.

Method of defining at least one treatment area including receiving a first set of data from a digital geometric representation of a target area; receiving a second set of data representing at least a portion of an applicator designed to contact the target area; digitally overlying the second set of data over the first set of data to generate a first digital overlay; digitally defining a treatment area on the first digital overlay surrounding the condition; generating a third set of data representing a portion of the applicator and the treatment area; digitally overlying the third set of data over the first set of data to generate a second digital overlay representing coverage of a condition by the treatment area; and generating a first electronic image that includes a visual depiction of the second digital overlay.