Akkasaligar et al., 2017 - Google Patents

Kidney stone detection in computed tomography images

Akkasaligar et al., 2017

Document ID
5811133994487937419
Author
Akkasaligar P
Biradar S
Kumbar V
Publication year
Publication venue
2017 International conference on smart technologies for smart nation (SmartTechCon)

External Links

Snippet

The proposed work is used to detect the kidney stones by using Level set segmentation method. Initially input images are preprocessed and region of interest is segmented. The level set segmentation is a good method to solve the problem of segmentation successfully …
Continue reading at ieeexplore.ieee.org (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
    • 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
    • G06T2207/10104—Positron emission tomography [PET]
    • 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
    • G06T2207/30—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
    • G06T2207/20—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
    • G06K9/62—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
    • G06T2207/10116—X-ray 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
    • G06T2207/20212—Image combination
    • G06T2207/20224—Image subtraction
    • 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
    • G06K9/62—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
    • 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
    • G06K2209/051—Recognition of patterns in medical or anatomical images of internal organs

Similar Documents

Publication Publication Date Title
Akkasaligar et al. Kidney stone detection in computed tomography images
Miranda et al. A survey of medical image classification techniques
EP4014201A1 (en) Three dimensional object segmentation of medical images localized with object detection
ur Rehman et al. An appraisal of nodules detection techniques for lung cancer in CT images
WO2007044508A2 (en) System and method for whole body landmark detection, segmentation and change quantification in digital images
Gomathi et al. Numerical function optimization in brain tumor regions using reconfigured multi-objective bat optimization algorithm
Kamra et al. Performance comparison of image segmentation techniques for lung nodule detection in CT images
Dave et al. Regional Kidney Stone Detection and Classification In Ultrasound Images
Sille et al. A Systematic Approach for Deep Learning Based Brain Tumor Segmentation.
Hasan et al. Lung Segmentation from Chest X-Ray Images Using Deeplabv3plus-Based CNN Model
Shanthi et al. Computer aided system for detection and classification of breast cancer
Santos et al. Detection of pathologic liver using ultrasound images
Kwong et al. A survey on deep learning approaches for breast cancer diagnosis
Mozaffari et al. 3D Ultrasound image segmentation: A Survey
Shanila et al. Segmentation of liver computed tomography images using dictionary-based snakes
Rajive Gandhi et al. A contrast adaptive histogram equalization with neural learning quantization (CAHE-NLQ) for blood clot detection in brain
Vasanthselvakumar et al. Detection and classification of kidney disorders using deep learning method
Noviana et al. Axial segmentation of lungs CT scan images using canny method and morphological operation
Shaziya et al. Comprehensive review of automatic lung segmentation techniques on pulmonary CT images
Devaki et al. A novel approach to detect fissures in lung CT images using marker-based watershed transformation
Abd Hamid et al. Incorporating attention mechanism in enhancing classification of alzheimer’s disease
Ragupathy et al. Gabor wavelet based detection of architectural distortion and mass in mammographic images and classification using adaptive neuro fuzzy inference system
Al-Saeed et al. Liver segmentation using fast-generalized fuzzy C-means (FG-FCM) from CT scans
El-Askary et al. Lung Nodule Detection and Classification using random forest: A review
Mangayarkarasi et al. Renal Anomalies through Ultrasound Imaging and Segmentation Techniques