A system including a hierarchical analytics framework that can utilize a first set of machine learned algorithms to identify and quantify a set of biological properties utilizing medical imaging data is provided. System can segment the medical imaging data based on the quantified biological properties to delineate existence of perivascular adipose tissue. The system can also segment the medical imaging data based on the quantified biological properties to determine a lumen boundary and/or determine a cap thickness based on a minimum distance between the lumen boundary and LRNC regions.

The invention concerns a method for obtaining operating parameters for x-ray imaging a patients maxillofacial region, the method comprising: —identifying a patients maxillofacial first region of interest ROI1, —determining a height of a horizontal plane of said patients maxillofacial first region of interest ROI1 when the patient is in an occlusion position or bites a patient positioning accessory, said horizontal plane passing through the teeth and the bones of the jaw, —acquiring through a slit-shaped collimator window a first set of data relative to said patients maxillofacial first region of interest ROI1 including the horizontal plane using x-ray CBCT imaging and a first x-ray dose, said first set of data being suitable for generating a CBCT slice, —reconstructing the CBCT slice comprising the horizontal plane based on the first set of data relative to the patients maxillofacial first region of interest ROI1, —obtaining operating parameters for an x-ray imaging apparatus based on the reconstructed CBCT slice in view of acquiring a second set of data of a patients maxillofacial second region of interest ROI2 using a second x-ray dose, the first x-ray dose being lower than the second x-ray dose.

The invention concerns a method for obtaining operating parameters for an x-ray CBCT imaging apparatus in view of acquiring a set of data of a patient's maxillofacial region. The method comprises: identifying a patient's maxillofacial first region of interest (ROI1), determining a height of a horizontal plane of said patient's maxillofacial first region of interest (ROI1) when the patient is in an occlusion position or bites a patient positioning accessory, acquiring through a slit-shaped collimator window a first set of data relative to said patient's maxillofacial first region of interest (ROI1) including the horizontal plane using x-ray CBCT imaging, reconstructing an axial CBCT slice comprising the horizontal plane based on the first set of data relative to the patient's maxillofacial first region of interest (ROI1), displaying the reconstructed axial CBCT slice of the patients maxillofacial first region of interest (ROI1) from the acquired first set of data, defining at least partially a second region of interest (ROI2) based on the displayed reconstructed axial CBCT slice of the patient's maxillofacial first region of interest (ROI1) and intersecting the latter, obtaining operating parameters for an x-ray CBCT imaging apparatus based on at least the defined second region of interest (ROI2) in view of acquiring a second set of data including the defined second region of interest (ROI2).

Systems and methods are disclosed for identifying features of a blood vessel using extravascular and intravascular images in order to estimate a virtual flow reserve (VFR) of the imaged blood vessel. Aspects of the disclosure include using extravascular images to estimate the size of the blood vessel in regions that have not been intravascularly imaged. The VFR estimation may be based on a resistance model that incorporates both the intravascular image data and the estimated blood vessel size. In other aspects, multiangled extravascular images are captured and analyzed in order to identify the size and orientation of branch vessels.

Techniques for determining a position of a native leaflet can include identifying a position of a mineral formation on the native leaflet before implantation of a prosthetic valve and analyzing an image representing the prosthetic valve implanted within the cardiac vessel. The analysis can identify a position of the mineral formation within the cardiac vessel after the prosthetic valve is implanted. Based on the position of the mineral formation on the native leaflet before implantation of the prosthetic valve and the position of the mineral formation within the cardiac vessel, a position of the native leaflet within the cardiac vessel can be determined.

The diagnosis support apparatus according to any of embodiments includes processing circuitry. The processing circuitry is configured to acquire external force data regarding external force applied to a subject. The processing circuitry is configured to generate diagnosis support data for supporting diagnosis practice to the subject based on the acquired external force data. The processing circuitry is configured to control output of the generated diagnosis support data.

A document creation support apparatus includes at least one processor, in which the processor is configured to derive properties for each of a plurality of predetermined property items in a structure of interest included in an image, generate a plurality of sentences describing the properties specified for at least one of the plurality of property items, and display each of the plurality of sentences, and display a described item, which is a property item of a property that is described in at least one of the plurality of sentences among the plurality of property items, on a display screen in an identifiable manner.

Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart, and create a three-dimensional model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient's heart and determine a fractional flow reserve within the patient's heart based on the three-dimensional model and the physics-based model.

A new chest X-ray database, referred to as “ChestX-ray8”, is disclosed herein, which comprises over 100,000 frontal view X-ray images of over 32,000 unique patients with the text-mined eight disease image labels (where each image can have multi-labels), from the associated radiological reports using natural language processing. We demonstrate that these commonly occurring thoracic diseases can be detected and spatially-located via a unified weakly supervised multi-label image classification and disease localization framework, which is validated using our disclosed dataset.

In one embodiment, a medical data processing apparatus includes processing circuitry. The processing circuitry obtains medical data relating to a subject, and outputs medical diagnostic image data obtained by performing predetermined processing on the medical data, along with standardized medical image data based on the medical data, the standardized medical image data being standardized for machine learning without performing part or all of the predetermined processing.