Sihare et al., 2022 - Google Patents
MRI-based tumour prediction based on U-Net and VGG-NetSihare et al., 2022
- Document ID
- 10019615912833833465
- Author
- Sihare S
- Dixit M
- Publication year
- Publication venue
- 2022 International Conference on Edge Computing and Applications (ICECAA)
External Links
Snippet
In the detection and treatment of life-threatening disorders, biomedical technology plays a critical role. Brain tumours have recently become one of the most frequent and dangerous disorders. The treatment of brain tumours is dependent on the experience and …
- 208000003174 Brain Neoplasms 0 abstract description 30
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
- G06T2207/30—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
- G06T2207/20—Special algorithmic details
- G06T2207/20112—Image segmentation details
-
- 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
- G06T2207/10072—Tomographic images
-
- 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
- G06T2207/10—Image acquisition modality
- G06T2207/10116—X-ray image
-
- 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
- G06K9/36—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
- G06T11/00—2D [Two Dimensional] image generation
-
- 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
-
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K2209/00—Indexing scheme relating to methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN110930367B (en) | Multi-modal ultrasound image classification method and breast cancer diagnosis device | |
Lo et al. | A multiple circular path convolution neural network system for detection of mammographic masses | |
Simaiya et al. | MRI brain tumour detection & image segmentation by hybrid hierarchical K-means clustering with FCM based machine learning model | |
EP4118617A1 (en) | Automated detection of tumors based on image processing | |
Hasan et al. | A modified convolutional neural networks model for medical image segmentation | |
Midya et al. | Computerized diagnosis of liver tumors from CT scans using a deep neural network approach | |
Rahman et al. | MRI brain tumor classification using deep convolutional neural network | |
Kumar et al. | A Deep Learning and Powerful Computational Framework for Brain Cancer MRI Image Recognition | |
Sihare et al. | MRI-based tumour prediction based on U-Net and VGG-Net | |
Maram et al. | Brain tumour detection on brats 2020 using u-net | |
Kumar et al. | Gannet devil optimization-based deep learning for skin lesion segmentation and identification | |
Ding et al. | Research on Spinal Canal GenerationMethod based on Vertebral Foramina Inpainting of Spinal CT Images by using BEGAN. | |
Miao et al. | Spinal neoplasm image inpainting with deep convolutional neutral networks | |
Barakala et al. | Brain Tumor Classification and Detection Using Machine Learning Algorithm | |
Kumar et al. | An efficient framework for brain cancer identification using deep learning | |
Chen et al. | MTGAN: mask and texture-driven generative adversarial network for lung nodule segmentation | |
Amritha et al. | Liver tumor segmentation and classification using deep learning | |
Ouassit et al. | Liver Segmentation | |
Kumar et al. | Multilevel Thresholding-based Medical Image Segmentation using Hybrid Particle Cuckoo Swarm Optimization | |
Neto | Deep Learning Based Analysis of Prostate Cancer from MP-MRI | |
Akshaya et al. | Identification of Brain Tumor on Mri images with and without Segmentation using DL Techniques | |
Gupta et al. | Lungs Disease Classification using VGG-16 architecture with PCA | |
EP3901903B1 (en) | Classifying a lesion based on longitudinal studies | |
Perumprath et al. | Deep Learning for Segmentation of Brain Tumors using MR Images based on U-Net Architecture | |
MOHIDEEN et al. | RECURRENT NEURAL NETWORK-BASED BRAIN TUMOR CLASSIFICATION USING 3D MAGNETIC RESONANCE IMAGING |