Disclosed is a magnetic resonance imaging apparatus and a magnetic resonance imaging method using same, the magnetic resonance imaging apparatus comprising: a pair of end coils disposed at the top and bottom ends, respectively, having a ring shape, and having a shape in which several spaces cut out of a circumferential shape are connected by switching module; a plurality of leg coils connecting the pair of end coils; and the switching module respectively disposed between the pair of end coils and the plurality of leg coils, wherein the switching module include a high frequency transmission/reception coil opened by a first frequency and shorted by a second frequency different from the first frequency.

The invention provides for a medical apparatus (100, 300, 400) comprising a subject support (102) configured for moving a subject (106) from a first position (124) to a second position (130) along a linear path (134). The subject support comprises a support surface (108) for receiving the subject. The subject support is further configured for positioning the subject support in at least one intermediate position (128). The subject support is configured for measuring a displacement (132) along the linear path between the first position and the at least one intermediate position. Each of the at least one intermediate position is located between the first position and the second position. The medical apparatus further comprises a camera (110) configured for imaging the support surface in the first position. Execution of machine executable instructions 116 cause the a processor (116) controlling the medical apparatus to: acquire (200) an initial image (142) with the camera when the subject support is in the first position; control (202) the subject support to move the subject support from the first position to the second position; acquire (204) at least one intermediate image (144) with the camera and the displacement for each of the at least one intermediate image as the subject support is moved from the first position to the second position; and calculate (206) a height profile (150, 600, 604) of the subject by comparing the initial image and the at least one intermediate image. The height profile is at least partially calculated using the displacement. The height profile is descriptive of the spatially dependent height of the subject above the support surface.

The invention provides for a medical apparatus (100, 300, 400) comprising a subject support (102) configured for moving a subject (106) from a first position (124) to a second position (130) along a linear path (134). The subject support comprises a support surface (108) for receiving the subject. The subject support is further configured for positioning the subject support in at least one intermediate position (128). The subject support is configured for measuring a displacement (132) along the linear path between the first position and the at least one intermediate position. Each of the at least one intermediate position is located between the first position and the second position. The medical apparatus further comprises a camera (110) configured for imaging the support surface in the first position. Execution of machine executable instructions 116 cause the a processor (116) controlling the medical apparatus to: acquire (200) an initial image (142) with the camera when the subject support is in the first position; control (202) the subject support to move the subject support from the first position to the second position; acquire (204) at least one intermediate image (144) with the camera and the displacement for each of the at least one intermediate image as the subject support is moved from the first position to the second position; and calculate (206) a height profile (150, 600, 604) of the subject by comparing the initial image and the at least one intermediate image. The height profile is at least partially calculated using the displacement. The height profile is descriptive of the spatially dependent height of the subject above the support surface.

A multi-member prosthesis including first and second elongated members and a central member, said multi-member prosthesis adapted to be advanced into a pilot SI joint opening in said dysfunctional SI joint via a posterior approach, the pilot SI joint opening comprising a sacrum opening and an ilium opening and a sacrum opening. The first elongated member adapted to be press-fit into the sacrum opening and the second elongated member adapted to be press-fit into the ilium opening. The central member including first and second elongated member securing means adapted to secure the first and second elongated members thereto.

A multi-member prosthesis including first and second elongated members and a central member, said multi-member prosthesis adapted to be advanced into a pilot SI joint opening in said dysfunctional SI joint via a posterior approach, the pilot SI joint opening comprising a sacrum opening and an ilium opening and a sacrum opening. The first elongated member adapted to be press-fit into the sacrum opening and the second elongated member adapted to be press-fit into the ilium opening. The central member including first and second elongated member securing means adapted to secure the first and second elongated members thereto.

Appropriate processing is executed in a method for excluding body motion data and image reconstruction according to a type and a characteristic of a body motion, so as to reduce an influence of the body motion, and prevent deterioration of image quality caused by exclusion of data generated during the body motion. An MRI apparatus includes a processing determination unit that collects k-space data and acquires body motion information from a sensor capable of detecting not only a respiratory motion but also general body motions, analyzes the body motion information obtained by the sensor, and branches and executes processing for subsequent data collection and image reconstruction according to the analysis result. The MRI apparatus determines, based on a temporal characteristic such as a duration and a frequency, and a spatial characteristic of the body motion, particularly a generation pattern in a k-space, body motion data to be excluded, and executes image reconstruction suitable for k-space data after exclusion of the body motion data.

A system is provided for augmenting a three-dimensional (3D) model of a heart to indicate the tissue state. The system accesses a 3D model of a heart, accesses two-dimensional (2D) images of tissue state slices of the heart, and accesses source location information of an arrhythmia. The system augments the 3D model with an indication of a source location based on the source location information. For each of a plurality of the tissue state slices of the heart, the system augments a 3D model slice of the 3D model that corresponds to that tissue state slice with an indication of the tissue state of the heart represented by the tissue state information of that tissue state slice. The system then displays a representation of the 3D model that indicates the source location of the arrhythmia and the tissue state of the heart.

A system is provided for augmenting a three-dimensional (3D) model of a heart to indicate the tissue state. The system accesses a 3D model of a heart, accesses two-dimensional (2D) images of tissue state slices of the heart, and accesses source location information of an arrhythmia. The system augments the 3D model with an indication of a source location based on the source location information. For each of a plurality of the tissue state slices of the heart, the system augments a 3D model slice of the 3D model that corresponds to that tissue state slice with an indication of the tissue state of the heart represented by the tissue state information of that tissue state slice. The system then displays a representation of the 3D model that indicates the source location of the arrhythmia and the tissue state of the heart.

A system and method for predicting mild cognitive impairment (MCI) related diagnosis and prognosis utilizing hybrid machine learning. More specifically, the system and method produce predictions of MCI conversions to dementia and prognosis related thereof. Using available medical imaging and non-imaging data a diagnosis and prognosis model is trained using transfer learning. A platform may then receive a request from a clinician for a target patient's diagnosis or prognosis. The target patient's medical data is retrieved and used to create a model for the target patient. Then details of the target patient's model and the diagnosis and prognosis model are compared, a prediction is generated, and the prediction is returned to the clinician. As new medical data becomes available it is fed into the respective model to improve accuracy and update predictions.

Systems and methods for improving soft tissue contrast, characterizing tissue, classifying phenotype, stratifying risk, and performing multi-scale modeling aided by multiple energy or contrast excitation and evaluation are provided. The systems and methods can include single and multi-phase acquisitions and broad and local spectrum imaging to assess atherosclerotic plaque tissues in the vessel wall and perivascular space.