Gamarra et al., 2020 - Google Patents
Image Processing Applied to Medical Science for the Study of Liver Cancer Using Segmentation in Magnetic Resonance ImagingGamarra et al., 2020
View PDF- Document ID
- 14285514860179142548
- Author
- Gamarra J
- Diaz O
- Publication year
- Publication venue
- Int. J. Info. Commun. Sci
External Links
Snippet
The objective to develop some algorithms with new techniques of image processing for the automatic segmentation of the liver using magnetic resonance images. The methodology is based in a descriptive description was proposed that allows to combine the information of …
- 230000011218 segmentation 0 title abstract description 54
Classifications
-
- 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
- G06T2207/10088—Magnetic resonance imaging [MRI]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20112—Image segmentation details
- G06T2207/20156—Automatic seed setting
-
- 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
- G06T2207/30048—Heart; Cardiac
-
- 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
- G06T2207/30024—Cell structures in vitro; Tissue sections in vitro
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20092—Interactive image processing based on input by user
- G06T2207/20104—Interactive definition of region of interest [ROI]
-
- 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
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
-
- 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
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20076—Probabilistic 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
- G06T2207/20—Special algorithmic details
- G06T2207/20048—Transform domain processing
-
- 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
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
-
- 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
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6267—Classification techniques
-
- 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
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6201—Matching; Proximity measures
- G06K9/6202—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/40—Analysis of texture
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Liu et al. | Segmentation of lung nodule in CT images based on mask R-CNN | |
Dahab et al. | Automated brain tumor detection and identification using image processing and probabilistic neural network techniques | |
Saez et al. | Model-based classification methods of global patterns in dermoscopic images | |
Ghosh et al. | Incorporating priors for medical image segmentation using a genetic algorithm | |
Aranguren et al. | Improving the segmentation of magnetic resonance brain images using the LSHADE optimization algorithm | |
CN110458859B (en) | Multi-sequence MRI-based multiple myeloma focus segmentation system | |
Linguraru et al. | Multi-organ segmentation from multi-phase abdominal CT via 4D graphs using enhancement, shape and location optimization | |
Yao et al. | Advances on pancreas segmentation: a review | |
Ge et al. | Unsupervised histological image registration using structural feature guided convolutional neural network | |
Ramasamy et al. | Segmentation of brain tumor using deep learning methods: a review | |
Liu et al. | Accurate and robust pulmonary nodule detection by 3D feature pyramid network with self-supervised feature learning | |
Cai et al. | Accurate weakly supervised deep lesion segmentation on CT scans: Self-paced 3D mask generation from RECIST | |
Almansour et al. | High-resolution MRI brain inpainting | |
Wu et al. | 3d centroidnet: nuclei centroid detection with vector flow voting | |
Jalab et al. | Fractional Renyi entropy image enhancement for deep segmentation of kidney MRI | |
Zhang et al. | Harmonizing pathological and normal pixels for pseudo-healthy synthesis | |
Delmoral et al. | Segmentation of pathological liver tissue with dilated fully convolutional networks: A preliminary study | |
Gamarra et al. | Image Processing Applied to Medical Science for the Study of Liver Cancer Using Segmentation in Magnetic Resonance Imaging | |
Ganasala et al. | Semiautomatic and automatic brain tumor segmentation methods: performance comparison | |
Kascenas et al. | Anomaly detection via context and local feature matching | |
Susomboon et al. | Automatic single-organ segmentation in computed tomography images | |
Yuan et al. | Automatic construction of filter tree by genetic programming for ultrasound guidance image segmentation | |
El–said | 3D medical image segmentation technique | |
Kumar et al. | Semiautomatic method for segmenting pedicles in vertebral radiographs | |
Carmo et al. | Extended 2d volumetric consensus hippocampus segmentation |