GLRLM-Based Feature Extraction for Acute Lymphoblastic Leukemia (ALL) Detection

被引：18

作者：

Mishra, Sonali ^{[1
]}

Majhi, Banshidhar ^{[1
]}

Sa, Pankaj Kumar ^{[1
]}

机构：

[1] Natl Inst Technol, Dept Comp Sci & Engn, Pattern Recognit Res Lab, Rourkela 769008, India

来源：

RECENT FINDINGS IN INTELLIGENT COMPUTING TECHNIQUES, VOL 2 | 2018年 / 708卷

关键词：

Acute Lymphoblastic Leukemia; Gray-level run length; Marker-based watershed segmentation; CAD system;

D O I：

10.1007/978-981-10-8636-6_41

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This work presents gray-level run length (GLRL) matrix as feature extraction technique for the classification of Acute Lymphoblastic Leukemia (ALL). ALL detection in an early stage is helpful in avoiding fatal hematopoietic ailment which might cause death. The GLRL matrix extracts textural features from the nucleus of the lymphocyte image which is used with Support Vector Machine (SVM) for classification. The public dataset ALL-IDB1 is used for the experiment, and we have obtained 96.97% accuracy for GLRL feature with SVM classifier.

引用

页码：399 / 407

页数：9

共 50 条

[1] LOCAL RELATIVE GLRLM-BASED TEXTURE FEATURE EXTRACTION FOR CLASSIFYING ULTRASOUND MEDICAL IMAGES
Sohail, Abu Sayeed Md.
Bhattacharya, Prabir
Mudur, Sudhir P.
Krishnamurthy, Srinivasan
2011 24TH CANADIAN CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING (CCECE), 2011, : 1092 - 1095
[2] Detection of Susceptibility to Childhood Acute Lymphoblastic Leukemia (ALL)
Tebbi, C.
PEDIATRIC BLOOD & CANCER, 2016, 63 : S119 - S119
[3] Detection of susceptibility to childhood Acute Lymphoblastic Leukemia (ALL)
Tebbi, Cameron K.
CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION, 2017, 26 (05)
[4] Texture feature based classification on microscopic blood smear for acute lymphoblastic leukemia detection
Mishra, Sonali
Majhi, Banshidhar
Sa, Pankaj Kumar
BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2019, 47 : 303 - 311
[5] Correlation based Feature Selection for Diagnosis of Acute Lymphoblastic Leukemia
Singhal, Vanika
Singh, Preety
PROCEEDING OF THE THIRD INTERNATIONAL SYMPOSIUM ON WOMEN IN COMPUTING AND INFORMATICS (WCI-2015), 2015, : 5 - 9
[6] Acute lymphoblastic leukemia (ALL) Preface
Advani, Anjali
BEST PRACTICE & RESEARCH CLINICAL HAEMATOLOGY, 2017, 30 (03) : 173 - 174
[7] PEDIATRIC ACUTE LYMPHOBLASTIC LEUKEMIA (ALL)
Anak, S. Sema
LEUKEMIA RESEARCH, 2014, 38 : S22 - S23
[8] Disease Detection Methodologies in Acute Lymphoblastic Leukemia (ALL): Opportunities for Improvement
Shalabi, Haneen
Yuan, Constance
Kulshreshtha, Amita
Dulau-Florea, Alina
Salem, Dalia
Gupta, Gaurav
Yates, Bonnie
Delbrook, Cindy
Derdak, Joanne
Mackall, Crystal L.
Lee, Daniel W.
Fry, Terry J.
Wayne, Alan
Stetler-Stevenson, Maryalice
Shah, Nirali N.
BIOLOGY OF BLOOD AND MARROW TRANSPLANTATION, 2019, 25 (03)
[9] Detection of homogeneous staining region (hsr) in acute lymphoblastic leukemia (ALL).
Xu, J
Ling, F
Dingle, B
AMERICAN JOURNAL OF HUMAN GENETICS, 2000, 67 (04) : 73 - 73
[10] A Robust Feature Extraction and Selection Method for the Recognition of Lymphocytes versus Acute Lymphoblastic Leukemia
Madhloom, Hayan T.
Kareem, Sameem Abdul
Ariffin, Hany
2012 INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER SCIENCE APPLICATIONS AND TECHNOLOGIES (ACSAT), 2012, : 330 - 335

← 1 2 3 4 5 →