Nothing Special   »   [go: up one dir, main page]

Gowthami et al., 2023 - Google Patents

A Study on Blood-Cell Segmentation Method for the Identification of Hematological Disorders

Gowthami et al., 2023

Document ID
13996445777362246147
Author
Gowthami M
Hemkumar D
Karthikeyan S
JohithSingarram S
Publication year
Publication venue
2023 9th International Conference on Advanced Computing and Communication Systems (ICACCS)

External Links

Snippet

A important task in the detection of hematological abnormalities is the automated segmentation of blood cells. It is essential for diagnosis, arranging treatments, and assessing results. This procedure uses a hybrid blood-cell segmentation technique based …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30004Biomedical image processing
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/0002Inspection of images, e.g. flaw detection
    • G06T7/0012Biomedical image inspection
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10024Color image
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00127Acquiring and recognising microscopic objects, e.g. biological cells and cellular parts
    • G06K9/00147Matching; Classification
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20112Image segmentation details
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34Computer-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
    • G06F19/345Medical expert systems, neural networks or other automated diagnosis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00221Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
    • G06K9/00268Feature extraction; Face representation
    • G06K9/00281Local features and components; Facial parts ; Occluding parts, e.g. glasses; Geometrical relationships
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6267Classification techniques
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46Extraction of features or characteristics of the image

Similar Documents

Publication Publication Date Title
Juneja et al. Automated detection of Glaucoma using deep learning convolution network (G-net)
Li et al. A large-scale database and a CNN model for attention-based glaucoma detection
Khojasteh et al. Fundus images analysis using deep features for detection of exudates, hemorrhages and microaneurysms
Kandhasamy et al. Diagnosis of diabetic retinopathy using multi level set segmentation algorithm with feature extraction using SVM with selective features
Wang et al. Human visual system-based fundus image quality assessment of portable fundus camera photographs
Akram et al. Identification and classification of microaneurysms for early detection of diabetic retinopathy
Dupas et al. Evaluation of automated fundus photograph analysis algorithms for detecting microaneurysms, haemorrhages and exudates, and of a computer-assisted diagnostic system for grading diabetic retinopathy
Kauppi Eye fundus image analysis for automatic detection of diabetic retinopathy
Chaum et al. Automated diagnosis of retinopathy by content-based image retrieval
WO2014109708A1 (en) A method and system for assessing fibrosis in a tissue
Seoud et al. Automatic grading of diabetic retinopathy on a public database
Khandouzi et al. Retinal vessel segmentation, a review of classic and deep methods
Khitran et al. Automated system for the detection of hypertensive retinopathy
Wong et al. Intelligent fusion of cup-to-disc ratio determination methods for glaucoma detection in ARGALI
Guo et al. EMFN: enhanced multi-feature fusion network for hard exudate detection in fundus images
Kadan et al. Detection of hard exudates using evolutionary feature selection in retinal fundus images
Dubey et al. Recent developments on computer aided systems for diagnosis of diabetic retinopathy: a review
Bouacheria et al. Automatic glaucoma screening using optic nerve head measurements and random forest classifier on fundus images
Sreng et al. Cotton wool spots detection in diabetic retinopathy based on adaptive thresholding and ant colony optimization coupling support vector machine
Rachapudi et al. Diabetic retinopathy detection by optimized deep learning model
Mukherjee et al. Predictive diagnosis of glaucoma based on analysis of focal notching along the neuro-retinal rim using machine learning
Dhivyaa et al. An effective detection mechanism for localizing macular region and grading maculopathy
Brancati et al. Segmentation of pigment signs in fundus images for retinitis pigmentosa analysis by using deep learning
Jung et al. Evaluating a deep-learning system for automatically calculating the stroke ASPECT score
Veras et al. SURF descriptor and pattern recognition techniques in automatic identification of pathological retinas