Moerth, 2022 - Google Patents
Scaling Up Medical Visualization: Multi-Modal, Multi-Patient, and Multi-Audience Approaches for Medical Data Exploration, Analysis and CommunicationMoerth, 2022
View PDF- Document ID
- 7238537329146956107
- Author
- Moerth E
- Publication year
External Links
Snippet
Medical visualization is one of the most application-oriented areas of visualization research. Close collaboration with medical experts is essential for interpreting medical imaging data and creating meaningful visualization techniques and visualization applications. Cancer is …
- 238000004458 analytical method 0 title abstract description 8
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
- G06F19/32—Medical data management, e.g. systems or protocols for archival or communication of medical images, computerised patient records or computerised general medical references
- G06F19/321—Management of medical image data, e.g. communication or archiving systems such as picture archiving and communication systems [PACS] or related medical protocols such as digital imaging and communications in medicine protocol [DICOM]; Editing of medical image data, e.g. adding diagnosis information
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
- G06F19/34—Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
- G06F19/345—Medical expert systems, neural networks or other automated diagnosis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10072—Tomographic images
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0012—Biomedical image inspection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2200/00—Indexing scheme for image data processing or generation, in general
- G06T2200/24—Indexing scheme for image data processing or generation, in general involving graphical user interfaces [GUIs]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T19/00—Manipulating 3D models or images for computer graphics
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
- G06Q50/10—Services
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Hosny et al. | Artificial intelligence in radiology | |
Andriole et al. | Optimizing analysis, visualization, and navigation of large image data sets: one 5000-section CT scan can ruin your whole day | |
US10025479B2 (en) | Advanced medical image processing wizard | |
EP3629898A1 (en) | Automated lesion detection, segmentation, and longitudinal identification | |
US12062429B2 (en) | Salient visual explanations of feature assessments by machine learning models | |
US11238197B1 (en) | Generating a 3D dataset containing a simulated surgical device | |
US10956635B1 (en) | Radiologist-assisted machine learning with interactive, volume subtending 3D cursor | |
US20170262584A1 (en) | Method for automatically generating representations of imaging data and interactive visual imaging reports (ivir) | |
Imran et al. | Fast and automatic segmentation of pulmonary lobes from chest CT using a progressive dense V-network | |
Oulefki et al. | Virtual Reality visualization for computerized COVID-19 lesion segmentation and interpretation | |
Katzmann et al. | Explaining clinical decision support systems in medical imaging using cycle-consistent activation maximization | |
Kelahan et al. | The radiologist’s gaze: mapping three-dimensional visual search in computed tomography of the abdomen and pelvis | |
Mörth et al. | Radex: Integrated visual exploration of multiparametric studies for radiomic tumor profiling | |
Amara et al. | Augmented reality visualization and interaction for covid-19 ct-scan nn automated segmentation: A validation study | |
US20210065900A1 (en) | Radiologist assisted machine learning | |
US11728035B1 (en) | Radiologist assisted machine learning | |
Hadler et al. | Introduction of Lazy Luna an automatic software-driven multilevel comparison of ventricular function quantification in cardiovascular magnetic resonance imaging | |
WO2023274599A1 (en) | Methods and systems for automated follow-up reading of medical image data | |
Moerth | Scaling Up Medical Visualization: Multi-Modal, Multi-Patient, and Multi-Audience Approaches for Medical Data Exploration, Analysis and Communication | |
Dzyubachyk et al. | Comparative exploration of whole-body MR through locally rigid transforms | |
Wu et al. | AI-Enhanced Virtual Reality in Medicine: A Comprehensive Survey | |
Skounakis et al. | DoctorEye: A multifunctional open platform for fast annotation and visualization of tumors in medical images | |
Hachaj et al. | Nowadays and future computer application in medicine | |
Paulo et al. | 3D Reconstruction from CT Images Using Free Software Tools | |
Marques | AI for Radiology |