A computerized system for monitoring cancer therapy and a related method. The system comprises an input port (IN) for receiving two or more input images acquired of a subject, the two or more input images capable of recording metabolic activity and extracellular pH level. An evaluator (EVAL) of the system is configured to assess, based on the input images, i) a change over time in metabolic activity and ii) a change over time in extracellular pH level. The evaluator (EVAL) is further configured to establish, based on the assessment, an indication on whether or not there is a response to a cancer therapy in relation to a lesion of the subject or on whether the assessment is inconclusive. The indication is output through an output interface (OUT).

Methods and systems for skull-based brain imaging. In some examples, a method includes receiving a first brain image of a brain taken at a first time and a second brain image of the brain taken at a second time; characterizing a structural change of brain tissue of the brain between the first time and the second time by: determining a global linear change of brain tissue using the first brain image and the second brain image; and determining a local deformation of brain tissue using the first brain image, the second brain image, and the global linear change of brain tissue; and outputting one or more parameters characterizing the structural change based on the global linear change of brain tissue and the local deformation of brain tissue.

A method for analysis of spine anatomy and stenosis is disclosed herein. The method includes preprocessing (3203) of images and then running segmentation models for each area of interest such as the foramen, disc, canal, vertebra (3206). In image post processing (3207), the system runs various heuristics to ensure accuracy (3208), computes areas (3209), and then runs a comparison model (3210). The report template produces HTML that is then converted to a PDF file of the final report (3214).

Apparatus for operating MRI is disclosed. The apparatus comprises: a control for operating an MRI scanner to carry out an MRI scan; an input for receiving first and second MRI scans respectively at the beginning and end of a predetermined time interval post contrast administration; a subtraction map former for forming a subtraction map from the first and the second MRI scans by analyzing the scans to distinguish between a population in which contrast clearance from the tissue is slower than contrast accumulation, and a population in which clearance is faster than accumulation; and an output to provide an indication of distribution of the populations. The control is configured to carry out the first scan at least five minutes and no more than twenty minutes post contrast administration and to carry out the second scan such that the predetermined time period is at least twenty minutes.

An apparatus includes: an acquisition unit configured to acquire pieces of three-dimensional data of a subject eye obtained at different times, the three-dimensional data including pieces of two-dimensional data obtained at different positions; a first planar alignment unit configured to perform first planar alignment including alignment between the pieces of three-dimensional data in a plane orthogonal to a depth direction of the subject eye; a first depth alignment unit configured to perform first depth alignment including alignment between pieces of two-dimensional data in at least one piece of three-dimensional data among the pieces of three-dimensional data and further including alignment between the pieces of three-dimensional data in the depth direction; and a generation unit configured to generate interpolation data of at least one piece of three-dimensional data among the pieces of three-dimensional data by using a result of the first planar alignment and a result of the first depth alignment.

A medical image processing apparatus includes an acquisition unit and a processing unit. The acquisition unit acquires first and second medical images in time series. The processing unit calculates a first parameter indicating a transition of luminance at a first point based on the luminance at the first point on the first medical image and luminance at a second point on the second medical image, calculates a second parameter indicating a transition of luminance at a third point based on the luminance at the third point on the first medical image and luminance at a fourth point on the second medical image, visualizes the first medical image by superimposing the first parameter on the first point and superimposing the second parameter on the third point; and visualizes the second medical image by superimposing the first parameter on the second point and superimposing the second parameter on the fourth point.

A method is provided. The method includes acquiring simultaneously multiple magnetic resonance (MR) images and multiple ultrasound images of an anatomical region of a subject over a scanned duration. The method also includes training an unsupervised deep learning-based deformable registration network. This training includes training a MR registration subnetwork based on the multiple MR images to generate MR deformation and transformation vectors, training an ultrasound registration subnetwork based on the multiple ultrasound images to generate ultrasound deformation and transformation vectors, and training a MR-to-ultrasound subnetwork based the multiple MR images and the multiple ultrasound images to generate MR-to-ultrasound deformation and transformation vectors between corresponding pairs of MR images and ultrasound images at each time point.

A method for precisely applying chemicals targeted by digital maps developed from remotely sensed data, including: obtaining EOS data through a growing season of a crop growing in a field; processing the EOS data to reflectance values, removing error-inducing effects of atmospheric alteration from the processed EOS data; calculating from the processed EOS data a crop performance index that indicates one or more poor performing area of the field; generating one or more maps of the crop performance index to allow a user to determine whether each of the one or more poor performing areas of the field are due to biological pests instead of topographic or soil constraints in discrete locations of the field; guiding the user to the one or more poor performing areas of the field using the one or more maps to allow the user to scout the one or more poor performing areas of the field to confirm and identify the biological pests; and providing guidance for a chemical application at the one or more poor performing areas that were confirmed as having the biological pests. Other embodiments are provided.

Embodiments predict early stage NSCLC recurrence, and include processors configured to access a pathology image of a region of tissue demonstrating early stage NSCLC; extract a set of pathomic features from the pathology image; access a radiological image of the region of tissue; extract a set of radiomic features from the radiological image; generate a combined feature set that includes at least one member of the set of pathomic features, and at least one member of the set of radiomic features; compute a probability that the region of tissue will experience NSCLC recurrence based, at least in part, on the combined feature set; and classify the region of tissue as recurrent or non-recurrent based, at least in part, on the probability. Embodiments may display the classification, or generate a personalized treatment plan based on the classification.

An endoscope system includes: an image acquiring unit that acquires a first frame image obtained by photographing a photographic subject and a second frame image obtained by photographing the photographic subject at a timing different from that of the first frame image; an oxygen saturation calculating unit that calculates an oxygen saturation by using the first frame image and the second frame image; a reliability calculating unit that calculates reliability of the oxygen saturation, calculated by the oxygen calculating unit, by using a signal ratio that is a ratio between a pixel value in a first specific wavelength range corresponding to a specific wavelength range of the first frame image and a pixel value in a second specific wavelength range corresponding to the specific wavelength range of the second frame image; and an information amount adjusting unit that adjusts an information amount of the oxygen saturation by using the reliability.