[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Vattikuti, 2022 - Google Patents

Comparative Analysis of Deep Learning Models for Tumor Detection in Medical Imaging

Vattikuti, 2022

View PDF
Document ID
1174366668848733690
Author
Vattikuti M
Publication year
Publication venue
Research-gate journal

External Links

Snippet

The rapid advancements in deep learning (DL) have revolutionized tumor detection in medical imaging, offering significant improvements in diagnostic accuracy and efficiency. This paper presents a comparative analysis of several state-of-the-art deep learning models …
Continue reading at research-gate.in (PDF) (other versions)

Classifications

    • 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
    • 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
    • G06T2207/30048—Heart; Cardiac
    • 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
    • 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
    • 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
    • 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
    • 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
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • 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
    • G06K2209/05—Recognition of patterns in medical or anatomical images
    • 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
Papadimitroulas et al. Artificial intelligence: Deep learning in oncological radiomics and challenges of interpretability and data harmonization
Yousef et al. A holistic overview of deep learning approach in medical imaging
Sahiner et al. Deep learning in medical imaging and radiation therapy
Mahmood et al. Breast lesions classifications of mammographic images using a deep convolutional neural network-based approach
Dabass et al. A convolution neural network with multi-level convolutional and attention learning for classification of cancer grades and tissue structures in colon histopathological images
Pillai Utilizing Deep Learning in Medical Image Analysis for Enhanced Diagnostic Accuracy and Patient Care: Challenges, Opportunities, and Ethical Implications
Vattikuti Comparative Analysis of Deep Learning Models for Tumor Detection in Medical Imaging
Maity et al. Automatic lung parenchyma segmentation using a deep convolutional neural network from chest X-rays
Wu et al. Self-supervised transfer learning framework driven by visual attention for benign–malignant lung nodule classification on chest CT
Thakur et al. Deep Learning Approaches for Medical Image Analysis and Diagnosis
Nazir et al. Machine Learning‐Based Lung Cancer Detection Using Multiview Image Registration and Fusion
Rodríguez et al. Computer aided detection and diagnosis in medical imaging: a review of clinical and educational applications
Jyotiyana et al. Deep learning and the future of biomedical image analysis
Tian et al. Radiomics and its clinical application: artificial intelligence and medical big data
Helaly et al. A review of deep learning approaches in clinical and healthcare systems based on medical image analysis
Alsadoon et al. DFCV: a framework for evaluation deep learning in early detection and classification of lung cancer
Crasta et al. A novel Deep Learning architecture for lung cancer detection and diagnosis from Computed Tomography image analysis
Dou et al. Automatic lesion detection with three-dimensional convolutional neural networks
Khalifa et al. Deep learning for image segmentation: a focus on medical imaging
Abdulwahhab et al. A review on medical image applications based on deep learning techniques
Agrawal et al. Deep learning models for medical image analysis: challenges and future directions
Salini et al. ViT: Quantifying Chest X-Ray Images Using Vision Transformer & XAI Technique
Przelaskowski et al. Semantic Segmentation of Abnormal Lung Areas on Chest X-rays to Detect COVID-19
Sarah et al. A novel approach to brain tumor detection using K-Means++, SGLDM, ResNet50, and synthetic data augmentation
Bolu Multimodal Deep Learning for Integrating Medical Image and Clinical Data: Enhancing Diagnostic and Predictive Capabilities