A diagnostic method for determining if a patient is viable candidate for a surgical procedure to permanently eliminate migraine headache pain. The method includes determining if a patient's pain is a migraine pain condition or pain from another medical condition and determining an anatomical location of the determined migraine pain condition. Once the anatomical location is determined, the method correlates the determined anatomical location of the migraine pain condition to a root cause nasal/sinus location and determines a root cause nasal/sinus condition that is causing the patient's migraine pain. Once these diagnostic procedures are complete, the patient may be scheduled for surgery to eliminate the root cause nasal/sinus condition, and thus, permanently eliminate the migraine headache pain.

The present disclosure provides an operation method of a PET (positron emission tomography) quantitative localization system, which includes steps as follows. The PET image and the MRI (magnetic resonance imaging) of the patient are acquired; the nonlinear deformation is performed on the MRI and the T1 template to generate deformation information parameters; the AAL (automated anatomical labeling) atlas is deformed to an individual brain space of the patient, so as to generate an individual brain space AAL atlas, where the AAL atlas and the T1 template are in a same space; lateralization indexes of the ROIs of the individual brain space AAL atlas corresponding to the PET image normalized through the gray-scale intensity are calculated; the lateralization indexes are inputted into one or more machine learning models to analyze the result of determining a target.

Systems and methods of detecting a presence of opacification or pneumatization in skeletal structures of patients are disclosed. The systems and methods include receiving images, processing the images using a convolutional neural network, and generating, with the convolutional neural network, an opacification score for the image. Systems and methods include training the convolutional neural network to delineate skeletal structure pixels within a computed tomography scan image and to generate an intensity value for each skeletal structure pixel within a computed tomography scan image to determine an opacification score for the computed tomography scan image.

The problem to be solved is to utilize an analysis result of a medical image that uses post-processing function to achieve a higher diagnosis accuracy. The medical image processing apparatus according to the present embodiment includes an acquirer that acquires a first medical image information which is a result of an external processing performed on a second medical information including a medical image, a receiver that receives a selected action for the first medical image information, and a register that associates and registers an action information about the selected action for the first medical image information with the first medical image information.

A method for automated analysis of data obtained from biologic, or non-biologic, material is provided. The method includes extracting, in a visualization of the material, first shapes that combine to form a target shape. The method also includes registering the first shape of the target shape to second shapes of a generic shape, and identifying variations between the first shapes and the second shapes. A system for analyzing biologic material is provided that includes an extraction engine a registration engine an identification engine a display an atlas adapted to provide the generic shape and a database for storing the visualization of the target shape. A non-transitory computer-readable medium storing a program for analyzing biologic material is provided. The program includes instructions that, when executed by a processor, causes a processor to execute the method.

In a method and system for providing visual information about a tumour location in human or animal body, an electromagnetic tumour sensor is provided in the tumour and tracked to determine its location in space, which is mapped to a tumour model. A surgical tool sensor is provided on a surgical tool, and tracked to determine its location in space, which is mapped to a surgical tool model. The body is scanned to obtain information about an anatomical structure. A reference sensor is provided on the body, and tracked to determine its location in space, which is mapped to the anatomical structure. A virtual image is displayed showing the tumour model, located with the at least one tumour sensor, in spatial relationship to the surgical tool model, located with the at least one surgical tool sensor, and the anatomical structure, located with the at least one reference sensor.

A system (100) includes a computer readable storage medium (122) with computer executable instructions (124), including: a biophysical simulator component (126) configured to determine a fractional flow reserve value via simulation and a traffic light engine (128) configured to track a user-interaction with the computing system at one or more points of the simulation to determine the fractional flow reserve value. A processor (120) is configured to execute the biophysical simulator component to determine the fractional flow reserve value and configured to execute the traffic light engine to track the user-interaction with respect to determining the fractional flow reserve value and provide a warning in response to determining there is a potential incorrect interaction. A display is configured to display the warning requesting verification to proceed with the simulation from the point, wherein the simulation is resumed only in response to the processor receiving the requested verification.

An information processing method includes deducing a diagnosis name derived from a medical image on the basis of an image feature amount corresponding to a value indicating a feature of a medical image, deducing an image finding representing a feature of the medical image on the basis of the image feature amount, and presenting the image finding deduced in the deducing the image finding which is affected by an image feature amount common to the image feature amount that has affected the deduction of the diagnosis name in the deducing the diagnosis name and the diagnosis name to a user.

A medical information processing apparatus includes processing circuitry. The processing circuitry is configured to acquire medical image data representing a blood vessel of a subject, extract a blood vessel shape from the medical image data, determine degree of meandering in each of regions from the extracted blood vessel shape, specify a deformed region in which the degree of meandering changes due to insertion of a device into the blood vessel on the basis of the degree of meandering, and output the deformed region in the blood vessel.

In accordance with one or more embodiments herein, a system for creating a decision support material indicating damage to at least a part of an anatomical joint of a patient, wherein the created decision support material comprises one or more damage images, is provided. The system comprises a storage media and at least one processor, wherein the at least one processor is configured to i) receive a series of radiology images of the at least part of the anatomical joint from the storage media; ii) obtain a three-dimensional image representation of the at least part of the anatomical joint which is based on at least a part of said series of radiology images, by generating said three-dimensional image representation in an image segmentation process based on said series of radiology images, or receiving said three-dimensional image representation from a storage media; iii) identify tissue parts of the anatomical joint in at least one of at least a part of said series of radiology images and/or the three-dimensional image representation using image analysis; iv) determine damage to the identified tissue parts in the anatomical joint by analyzing at least one of at least a part of said series of radiology images and/or the three-dimensional image representation of the at least part of the anatomical joint; v) determine suitable sizes and suitable implanting positions for one or more graft plugs based on the determined damage; vi) mark damage to the anatomical joint and suitable sizes and implanting positions for the one or more graft plugs in the obtained three-dimensional image representation of the anatomical joint; and vii) generate a decision support material, where the determined damage to the at least part of the anatomical joint and the suitable sizes and implanting positions for the one or more graft plugs are marked in at least one of the one or more damage images of the decision support material, and at least one of the one or more damage images is generated based on the obtained three-dimensional image representation of the at least part of the anatomical joint.