Patent classifications
A61B6/032
Systems and methods for scanning a patient in an imaging system
The present disclosure relates to a method for scanning a patient in an imaging system. The imaging system may include one or more cameras directed at the patient. The method may include obtaining a position of each of the camera(s) relative to the imaging system. The method may also include obtain image data of the patient captured by the camera(s), wherein the image data may correspond to a first view with respect to the patient. The method may further include generating projection image data of the patient based on the image data and the position of each of the camera(s) relative to the imaging system, wherein the projection image data may correspond to a second view with respect to the patient different from the first view. The method may further include generating control information for scanning the patient based on the projection image data of the patient.
Method of using lung airway carina locations to improve ENB registration
Disclosed are systems, devices, and methods for registering a luminal network to a 3D model of the luminal network. An example method comprises generating a 3D model of a luminal network, identifying a target within the 3D model, determining locations of a plurality of carinas in the luminal network proximate the target, displaying guidance for navigating a location sensor within the luminal network, tracking the location of the location sensor, comparing the tracked locations of the location sensor and the portions of the 3D model representative of open space, displaying guidance for navigating the location sensor a predetermined distance into each lumen originating at the plurality of carinas proximate the target, tracking the location of the location sensor while the location sensor is navigated into each lumen, and updating the registration of the 3D model with the luminal network based on the tracked locations of the location sensor.
System and method for navigating within the lung
Methods and systems for navigating to a target through a patient's bronchial tree are disclosed including a bronchoscope, a probe insertable into a working channel of the bronchoscope and including a location sensor, and a workstation in operative communication with the probe and the bronchoscope, the workstation including a user interface that guides a user through a navigation plan and is configured to present a central navigation view including a plurality of views configured for assisting the user in navigating the bronchoscope through central airways of the patient's bronchial tree toward the target, a peripheral navigation view including a plurality of views configured for assisting the user in navigating the probe through peripheral airways of the patient's bronchial tree to the target, and a target alignment view including a plurality of views configured for assisting the user in aligning a distal tip of the probe with the target.
3-D convolutional autoencoder for low-dose CT via transfer learning from a 2-D trained network
A 3-D convolutional autoencoder for low-dose CT via transfer learning from a 2-D trained network is described, A machine learning method for low dose computed tomography (LDCT) image correction is provided. The method includes training, by a training circuitry, a neural network (NN) based, at least in part, on two-dimensional (2-D) training data. The 2-D training data includes a plurality of 2-D training image pairs. Each 2-D image pair includes one training input image and one corresponding target output image. The training includes adjusting at least one of a plurality of 2-D weights based, at least in part, on an objective function. The method further includes refining, by the training circuitry, the NN based, at least in part, on three-dimensional (3-D) training data. The 3-D training data includes a plurality of 3-D training image pairs. Each 3-D training image pair includes a plurality of adjacent 2-D training input images and at least one corresponding target output image. The refining includes adjusting at least one of a plurality of 3-D weights based, at least in part, on the plurality of 2-D weights and based, at least in part, on the objective function. The plurality of 2-D weights includes the at least one adjusted 2-D weight.
SYSTEMS AND METHODS FOR ROBOTICALLY-ASSISTED HISTOTRIPSY TARGETING BASED ON MRI/CT SCANS TAKEN PRIOR TO TREATMENT
Methods and devices for producing cavitation in tissue are provided. Methods and devices are also provided for surgical navigation, including defining a target treatment zone and navigating a focus of a therapy transducer to the target treatment zone. Embodiments are provided for co-registering a plurality of surgical imaging and navigation systems. Systems for performing Histotripsy therapy are also discussed.
SCANNER AND METHOD OF IMAGE RECONSTRUCTION
Provided herein is technology relating to radiology and radiotherapy and particularly, but not exclusively, to apparatuses, methods, and systems for multi-axis medical imaging of patients in vertical and horizontal positions with single or dual energy acquisition.
SYSTEM AND METHOD FOR FLOW-RESOLVED, THREE-DIMENSIONAL IMAGING
A system and method are provided for creating an image including quantified flow within vessels of a subject. The method includes providing a single-sweep, three-dimensional (3D) image volume acquired from a subject during a single pass of a computed tomography (CT) imaging system as the subject receives a dose of a contrast agent and determining a phase shift corresponding to pulsatile contrast in vessels within the single-sweep, 3D image volume. The method further includes quantifying a flow through the vessels within the single-sweep, 3D image volume using the phase shift and generating a report including indicating flow through the vessels within the 3D image volume.
Limited data persistence in a medical imaging workflow
A medical imaging system comprises an operator terminal configured to obtain at least one image of a patient generated by a medical imaging device, receive one or more notes pertaining to the at least one image from an operator of the medical imaging device, store a clean set of images including the at least one image in at least one server, annotate the at least one image with the one or more notes to generate a set of annotated images; tag the set of annotated images as non-persistent, and store the set of annotated images in the at least one server; wherein the at least one server is configured to provide to a physician terminal both the clean set of images and the annotated set of images stored for the patient and automatically delete the one or more images tagged as non-persistent after review thereof by the physician.
Tooth modeling system
Systems and methods are disclosed for treating teeth to correct for malocclusions. This may be accomplished by applying a series of labels to a digital dental model and applying a rolling ball process to identify tooth boundaries separating one tooth from a neighboring tooth and to also determine the crown/gum margin. The user may further assign regions to the dental model to indicate hard regions and soft regions. With the dental model labeled and defined, the user may then generate a treatment plan for moving the labeled and defined tooth or teeth relative to one another to correct for any malocclusions. Upon approval of the treatment plan, a series of 3D printed dental appliances or aligners to be worn in series by the patient may be fabricated to ultimately move the tooth or teeth to a desired position.
System and method for estimating vascular flow using CT imaging
A system and method for estimating vascular flow using CT imaging include a computer readable storage medium having stored thereon a computer program comprising instructions, which, when executed by a computer, cause the computer to acquire a first set of data comprising anatomical information of an imaging subject, the anatomical information comprises information of at least one vessel. The instructions further cause the computer to process the anatomical information to generate an image volume comprising the at least one vessel, generate hemodynamic information based on the image volume, and acquire a second set of data of the imaging subject. The computer is also caused to generate an image comprising the hemodynamic information in combination with a visualization based on the second set of data.