Johns Hopkins University

Animetrics, Inc.

Terumo Medical Corporation

Michael I Miller

Susumu Mori

Kenichi Oishi

Jiangyang Zhang

Anqi Qiu

Andreia V Faria

Mark Eberhardt

Yasutake Yamada

Hiroyoshi Ise

Stewart Mostofsky

George Stern

Benjamin Dirlikov

Husexin Fertac Bilge

Xiaoying Tang

Elie Laurent Younes

Can Ceritoglu

An embodiment in accordance with the present invention provides a system and method for a three-dimensional interface for interacting with a database. The three-dimensional interface can include an interactive three-dimensional atlas depicting an element of anatomy, machine, device, or other object. Given the three-dimensional nature of the atlas, a user can zoom in on particular areas to view them with more specificity. Different structural points of the anatomy are labeled with names or coordinates, such that the user can select one of the structural points and search a database for information related to that specific structural point. The user can also use specific keywords to search with respect to the specific structural point selected. The three-dimensional interface and atlas are displayed to the user on a computing device that can either house the database within its memory or alternately communicate with the database over a network.

Query-based three-dimensional atlas for accessing image-related data

A non-invasive imaging system, including an imaging scanner suitable to generate an imaging signal from a tissue region of a subject under observation, the tissue region having at least one substructure; a signal processing system in communication with the imaging scanner to receive the imaging signal from the imaging scanner; and a data storage unit in communication with the signal processing system, wherein the data storage unit stores an anatomical atlas comprising data encoding spatial information of the at least one substructure in the tissue region, and a pathological atlas corresponding to an abnormality of the tissue region, wherein the signal processing system is adapted to automatically identify, using the imaging signal, the anatomical atlas, and the pathological atlas, a presence of the abnormality or a pre-cursor abnormality in the subject under observation.

Intelligent atlas for automatic image analysis of magnetic resonance imaging

A computer-implemented method, a computer system and a non-transitory computer-readable medium for constructing human-readable sentences from imaging data of a subject can include: receiving imaging data including image elements of at least one region of interest of the subject; segmenting the imaging data of the region of interest into a plurality of sub-regions, where each sub-region includes a portion of the image elements; calculating an abnormality factor for each of the sub-regions by quantitatively analyzing segmented image information of the imaging data of the sub-regions using data from a normal database; comparing each abnormality factor to a threshold value; constructing a human-understandable sentence for the subject when a corresponding abnormality factor exceeds the threshold, where each human-understandable sentence references a physical structure threshold associated with the calculation for the region or sub-region; and outputting the human-understandable sentences for the at least one region of the subject.

Automated generation of sentence-based descriptors from imaging data

A computer-implemented method, system and non-transitory computer readable storage medium for classifying a region of interest of a subject, including receiving imaging data comprising at least one image element, the imaging data comprising the region of interest of the subject; providing a plurality of atlases, each of the plurality of atlases having a candidate region that corresponds to the region of interest of the imaging data, each of the plurality of atlases having at least one image element with associated location and property information; co-registering the plurality of atlases to the imaging data, using at least one processor; assigning a probability to generate a labeling parameter for the region of interest, the probability being associated with each atlas; and classifying the region of interest of the subject based on the assigning.

Automated anatomical labeling by multi-contrast diffeomorphic probability fusion

The present invention is directed to a computer application for analyzing handwriting. The handwriting is digitized by being captured by a computing device such as a tablet. The application analyzes four components of the digitized handwriting. The initial component provides real-time writing speed feedback to the subject. The second fully automated component computes a variety of kinematic measures based on periods of time when the subject is writing versus the pen being off the tablet. A third component is able to concatenate pen strokes into user defined characters and assesses character and/or word spacing based on preset distances. For the fourth component, a 2-dimensional version of the large deformation diffeomorphic metric mapping (LDDMM) method is used to compare each character to a template character. Together, these components can be used to assess handwriting for a broad range of applications.

Kinematic and morpometric analysis of digitized handwriting tracings

Computer systems, computer-implemented methods, and non-transitory computer readable storage media for gross feature recognition including receiving an image comprising a plurality of image elements representing the region of interest of the subject. Gross feature recognition can further include co-registering the image to an atlas to segment the plurality of image elements into a plurality of sub-regions corresponding to structures in the atlas, where the structures in the atlas are ordered in a first rank order according to a predetermined feature. Further included can be ordering the plurality of sub-regions in a second rank order according to the predetermined feature. Further included can be identifying as gross features one or more of the plurality of sub-regions whose positions in the first rank order of the ordered sub-regions differ from positions in the second rank order of the corresponding ordered structures in the atlas.

Gross feature recognition of anatomical images based on atlas grid

A method, computer system and computer readable storage medium for searching for one or more images having a region of interest similar to the region of a subject, including: receiving imaging data comprising a plurality of image elements of the region of interest of the subject; segmenting the imaging data of the region of interest of the subject into a plurality of sub-regions corresponding to various structures at a plurality of levels of granularity, the plurality of levels of granularity having a relationship such that a level of granularity has fewer structures at a lower level of granularity; and calculating at each of the plurality of levels of granularity an abnormality factor or risk factor for the segmented various structures of said region of interest, to provide a segmented said region of interest of said subject with at least one of said abnormality factor or risk factor associated therewith.

Methods and systems for analyzing anatomy from multiple granularity levels

A non-invasive imaging system, including: a non-invasive imaging scanner; a signal processing unit in communication with the imaging scanner to receive an imaging signal from a subject under observation; and a data storage unit in communication with the signal processing unit, wherein the data storage unit stores template data corresponding to a tissue region of the subject, and wherein the signal processing unit is adapted to generate a surface map to encode a property of a subvolume of the tissue region using the template data.

Automated surface-based anatomical analysis based on atlas-based segmentation of medical imaging

A method may include standardizing an input image to produce a standardized input image; structurizing the standardized input image to be characterized by a plurality of anatomical properties; mapping the input image to one or more reference cases of a plurality of reference cases using the plurality of anatomical properties, wherein the one or more reference cases are associated with first non-image clinical information; and determining second non-image clinical information for the input image based on the one or more reference cases and the first non-image clinical information.

Bioimaging grid

The present technology is directed to a dilator centering device and assemblies and methods using same. In particular, a dilator centering device in accordance with the disclosed technology can be used with a sheath hub assembly. In one embodiment, a dilator centering device includes a lumen capable of receiving a dilator shaft and centering a dilator shaft with respect to the sheath hub as the dilator shaft enters the sheath hub. In one embodiment, the dilator centering device can be attached to the sheath hub during manufacturing or it can be attached at the use site. In one embodiment, the dilator centering device can be integrated with and non-removable from the sheath hub. The embodiments disclosed herein are illustrative and do not limit the scope and spirit of the disclosed technology.

Dilator centering device and assemblies

An embodiment of the current invention includes a non-invasive imaging system, comprising: an imaging scanner suitable to generate an image representing a tissue region of a subject under observation, the tissue region having at least one substructure and the image comprising a plurality of image voxels; a signal processing system in communication with the imaging scanner to receive the imaging signal from the imaging scanner; and a data storage unit in communication with the signal processing system, wherein the data storage unit is configured to store: an atlas comprising spatial information of the at least one substructure in the tissue region, and a database comprising a plurality of pre-stored medical images representing the tissue region, and wherein the signal processing system is adapted to: identify, based on the atlas and for each of the at least one substructure, a corresponding portion of image voxels in the image; provide a computed quantification of the corresponding portion of image voxels for each of the at least one substructure of the tissue region by performing spatial filtering on the image; and search the database to provide at least one selected medical image from the plurality of pre-stored medical images, the at least one selected medical image having a corresponding quantification that is substantially similar to the computed quantification.

Image search engine

A non-invasive imaging system, including an imaging scanner suitable to generate an imaging signal from a tissue region of a subject under observation, the tissue region having at least one anatomical substructure and more than one constituent tissue type; a signal processing system in communication with the imaging scanner to receive the imaging signal from the imaging scanner; and a data storage unit in communication with the signal processing system, wherein the data storage unit is configured to store a parcellation atlas comprising spatial information of the at least one substructure in the tissue region, wherein the signal processing system is adapted to: reconstruct an image of the tissue region based on the imaging signal; parcellate, based on the parcellation atlas, the at least one anatomical substructure in the image; segment the more than one constituent tissue types in the image; and automatically identify, in the image, a portion of the at least one anatomical substructure that correspond to one of the more than one constituent tissue type.

Atlas-based analysis for image-based anatomic and functional data of organism

A magnetic resonance imaging (MRI) system, comprising: a magnetic resonance imaging scanner configured to generate a plurality of signals for forming at least one magnetic resonance image of a soft tissue region from a subject under observation, wherein the at least one magnetic resonance image provides at least one integrating feature to facilitate automatic segmentation; a signal processing system in communication with the magnetic resonance imaging scanner to receive the plurality of signals; and a data storage unit in communication with the signal processing system, wherein the data storage unit contains at least one template corresponding to the soft tissue region, wherein the signal processing system is adapted to process the plurality of signals received from the magnetic resonance imaging scanner to automatically perform segmentation for the soft tissue region of the subject under observation by utilizing the at least one template and the at least one integrating feature.

Automated image analysis for magnetic resonance imaging

A non-invasive imaging system, comprising: an imaging scanner; a signal processing system in communication with the imaging scanner to receive an imaging signal from the imaging scanner; and a data storage unit in communication with the signal processing system, wherein the data storage unit stores template data corresponding to a tissue region of a subject under observation, wherein the signal processing system is adapted to compute, using the imaging signal and the template data, refined template data corresponding to the tissue region, and wherein the refined template data incorporates subpopulation variability information associated with the tissue region such that the signal processing system provides an image of the tissue region in which a substructure is automatically identified taking into account the subpopulation variability information.

Advanced cost functions for image registration for automated image analysis: multi-channel, hypertemplate and atlas with built-in variability

A non-invasive medical imaging system includes: an imaging scanner capable of generating an imaging signal from a subject under observation inside the imaging scanner; a signal processing system in communication with the imaging scanner, and a data storage unit in communication with the signal processing system, wherein the data storage unit is suitable for storing a first image corresponding to a tissue region of the subject, wherein the signal processing system is capable of generating a second image encoding the tissue region of the subject by performing a reconstruction based on the imaging signal, the imaging signal acquired at a later time than the first image; wherein the signal processing system is constructed to receive the imaging signal from the imaging scanner and the first image from the data storage unit respectively, wherein the signal processing system is adapted to provide a registered first image by registering the first image to the second image via a transformation in a space of diffeomorphism, wherein the signal processing system is further adapted to compute a difference image between the second image and the registered first image; and wherein the signal processing system is further adapted to output the difference image.

Growing community of inventors

Towson, MD, United States of America

Michael I Miller