[go: up one dir, main page]

Gavarraju et al., 2024 - Google Patents

Integrating Multimodal Medical Imaging Data for Enhanced Bone Cancer Detection: A Deep Learning-Based Feature Fusion Approach

Gavarraju et al., 2024

View PDF
Document ID
1218135042162907014
Author
Gavarraju L
Rao A
Anusha R
Reddy D
Anantula J
Surendra D
Publication year
Publication venue
Journal of Theoretical and Applied Information Technology

External Links

Snippet

Early detection and treatment planning depend on accurate bone cancer detection. Using deep learning-based feature fusion techniques, we propose a novel approach for improving bone cancer detection using multimodal medical imaging data. The method enhances the …
Continue reading at www.jatit.org (PDF) (other versions)

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
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0012—Biomedical image inspection
    • 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
    • G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • 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
    • 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
    • G06T2207/20—Special algorithmic details
    • G06T2207/20112—Image segmentation details
    • 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
    • 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
    • G06K9/00127—Acquiring and recognising microscopic objects, e.g. biological cells and cellular parts
    • 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
    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass

Similar Documents

Publication Publication Date Title
Silva-Rodríguez et al. Going deeper through the Gleason scoring scale: An automatic end-to-end system for histology prostate grading and cribriform pattern detection
Sori et al. Multi-path convolutional neural network for lung cancer detection
US20210225511A1 (en) Method and system for improving cancer detection using deep learning
Masood et al. Brain MRI analysis using deep neural network for medical of internet things applications
Alabdulkreem et al. Bone cancer detection and classification using owl search algorithm with deep learning on X-ray images
Miah et al. Advancing brain tumor detection: a thorough investigation of CNNs, clustering, and softmax classification in the analysis of MRI images
Almutairi et al. An Efficient USE‐Net Deep Learning Model for Cancer Detection
Isfahani et al. Presentation of novel hybrid algorithm for detection and classification of breast cancer using growth region method and probabilistic neural network
Madhukar et al. Classification of breast cancer using ensemble filter feature selection with triplet attention based efficient net classifier.
Barbhuiya et al. Application of convolutional neural networks in cancer diagnosis
Akram et al. Recognizing breast cancer using edge-weighted texture features of histopathology images
Ghosh et al. Lung nodule classification using mobilenet transfer learning
Avanija et al. Interpretation of brain tumour using deep learning model
Dass et al. A novel approach for small object detection in medical images through deep ensemble convolution neural network
Raza et al. Visual explanations: Activation-based acute lymphoblastic leukemia cell classification
Raju et al. A contemporary technique for lung disease prediction using deep learning
Solanki et al. An approach for classification of brain tumor using fully connected deep convolutional neural network
Mustapha et al. Leveraging the novel MSHA model: A focus on adrenocortical carcinoma
Gavarraju et al. Integrating Multimodal Medical Imaging Data for Enhanced Bone Cancer Detection: A Deep Learning-Based Feature Fusion Approach
Rani et al. RETRACTED: Accurate artificial intelligence method for abnormality detection of CT liver images
Shaikh et al. Improved skin cancer detection using CNN
Muñoz-Chavez et al. Detection of breast cancer in mammography using pretrained convolutional neural networks with fine-tuning
Babu et al. Diagnosis of lung cancer detection using various deep learning models: A survey
Vishwakarma et al. Segmentation and detection of brain tumors using efficientnetb3 model
Amanullah et al. Convolutional neural network-based MRI brain tumor classification system