Disclosed are methods, apparatuses and software products for graphic processing using a visual display system and image analysis for sizing of surgical implants in the planning and execution of spinal surgery, such as spinal fusion surgery of the cervical spine. The graphic processing includes determining a trajectory line for one or more target spine levels captured and measured by one or more measuring system to generate a 3D motion dataset for use in a range of diagnostic and therapeutic applications.

A method of generating biomarker parameters includes acquiring imaging data depicting a patient using a MRI system. The imaging data is acquired for a plurality of contrasts resulting from application of a pulse on the patient's anatomy. A process is executed to generate a MoCoAve image for each contrast. This process includes dividing the imaging data for the contrast into bins corresponding to one of a plurality of respiratory motion phases, and reconstructing the imaging data in each bin to yield bin images. The process further includes selecting a reference bin image from the bin images, and warping the bin images based on the reference bin image. The warped bin images and the reference bin image are averaged to generate the MoCoAve image for the contrast. One or more biomarker parameter maps are calculated based on the MoCoAve images generated for the contrasts.

There are provided an ophthalmologic information analysis apparatus and an ophthalmologic information analysis program capable of efficiently performing follow-up observation of a subject eye. There is provided: a central processing unit configured to:

acquire first analysis data obtained by analyzing an analysis region of the subject eye in first OCT data including the analysis region; acquire second OCT data captured on a day different from that of the first OCT data; perform an analysis comprising: specifying the analysis region corresponding to the first analysis data from the second OCT data; and acquiring second analysis data obtained by analyzing the analysis region in the second OCT data; and control a display to display the first analysis data and the second analysis data in a comparable manner.

Devices, systems, and methods for evaluating blood flow with vascular perfusion imaging are disclosed. In an embodiment, a medical system is disclosed. One embodiment of the medical system comprises a perfusion imaging system configured to obtain perfusion imaging data associated with movement of contrast through a vessel of a patient, a graphical user interface, and a medical processing unit in communication with the perfusion imaging system and the graphical user interface. The medical processing unit is configured to receive a first set of perfusion imaging data from the perfusion imaging system, determine at least one parameter representative of the movement of the contrast through the vessel of the patient, generate a first graphical representation of the first set of perfusion imaging data and the at least one parameter determined based on the first set of perfusion imaging data, and output the first graphical representation to the graphical user interface.

Disclosed are an unsupervised learning-based image registration method using a neural network with cycle consistency and an apparatus therefor. An image registration method includes receiving a first image and a second image for image registration, outputting a deformation field for the first image and the second image using an unsupervised learning-based neural network with cycle consistency for the deformation field, and generating a registration image for the first image and the second image based on a spatial deformation function using the output deformation field. The outputting of the deformation field includes outputting the deformation field for the first image for registering the first image to the second image may be output, when the first image is a moving image and the second image is a fixed image, and the generating of the registration image includes generating the registration image by applying the deformation field for the first image to the first image using the spatial deformation function.

The present disclosure provides a method for treating clinical or pre-clinical skin damage in a skin field of a subject, wherein the skin field has been allocated a skin cancerization field index (SCFI) score of at least 1 as determined by a process comprising the steps of: (i) assessing the number of keratoses in the skin field; (ii) assessing the thickness of the thickest keratosis in the skin field; and (iii) assessing the proportion of the field affected by clinical or subclinical skin damage. Based on the assessments made in (i), (ii) and (iii) the subject is optionally treated by at least one of (a) freezing one or more lesions, (b) shaving, curetting or surgically removing one or more lesions, (c) applying a topical treatment for actinic keratosis, basal cell carcinoma or squamous cell carcinoma, and (d) radiation therapy.

A method for determining MRI biomarkers for in vivo issue includes the steps of obtaining raw data concerning the in vivo tissue from a MRI machine; processing the raw data to obtain parameter maps; when applicable, registering images such that the exact same tissue at serial points can be analyzed; applying a grid over a region of interest to create sub-regions of interest (SROIs); inserting parameter measures for each SROI into a spreadsheet program to create a large 3D data matrix; applying standard big-data analytics including data mining and statistics of matrix measures to find patterns of measurement values or measure changes (which may include established biomarkers). A medical imaging software program is used to obtain the parameter maps from the raw data and place multiple grids over the SROIs. 3D matrix measures may be data mined and analyzed using standard big-data analytics.

A division unit 22 divides a brain included in a first brain image into a plurality of regions by performing registration between the first brain image including a brain of a subject and a standard brain image divided into a plurality of regions. A registration unit 23 performs registration between the first brain image and a second brain image that includes the brain of the subject and has a different imaging date and time from the first brain image. A change amount acquisition unit 24 acquires the amount of change from a corresponding region in the brain included in the first brain image, for at least one region of the plurality of regions in the brain included in the second brain image, based on the registration result.

Systems and methods for determining bacterial load in targets are disclosed. An autofluorescence detection and collection device includes a light source configured to illuminate a target with excitation light causing at least one biomarker in the illuminated target to fluoresce. Bacterial autofluorescence data regarding the target is collected and analyzed to determine bacterial load the target. The autofluorescence data may be analyzed using pixel intensity.

A method for determining respiratory induced blood mass change from a four-dimensional computed tomography (4D CT) includes receiving a 4D CT image set which contains a first three-dimensional computed tomographic image (3D CT) and a second 3D CT image. The method includes executing a deformable image registration (DIR) function on the received 4D CT image set, and determining a displacement vector field indicative of the lung motion induced by patient respiration. The method further includes segmenting the received 3D CT images into a first segmented image and a second segmented. The method includes determining the change in blood mass between the first 3D CT image and the second 3D CT image from the DIR solution, the segmented images, and measured CT densities.