Effectiveness of Region Growing Based Segmentation Technique for Various Medical Images - A Study

被引:1
|
作者
Dabass, Manju [1 ]
Vashisth, Sharda [1 ]
Vig, Rekha [1 ]
机构
[1] NorthCap Univ, Gurgaon 121102, Haryana, India
来源
DATA SCIENCE AND ANALYTICS | 2018年 / 799卷
关键词
Biomedical image processing; Image segmentation; Threshold; Region growing; AUTOMATIC LUNG SEGMENTATION; BLOOD-VESSELS; RETINAL IMAGES; MATCHED-FILTER; CLASSIFICATION; GALLBLADDER; EXTRACTION; BENIGN; LEVEL; CT;
D O I
10.1007/978-981-10-8527-7_21
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Due to rapid and continuous progress along with higher fidelity rate, medical imaging is becoming one of the most crucial fields in scientific imaging. Both microscopic and macroscopic modalities are probed and their resulting images are analyzed and interpreted in medical imaging for the early detection, diagnosis, and treatment of various ailments like a tumor, cancer, gallstones, etc. Although the field of medical image processing is growing significantly and persistently, there still exist a number of challenges in this field. Among these challenges, the frequently occurring and critically significant one is image segmentation. The theme work presented in this paper includes challenges involved and comparative analysis of segmentation using region growing techniques frequently utilized in various biomedical images like retinal vessel image, mammograms, magnetic resonance images, PET-CT image, coronary artery image, microscopy image, ultrasound image, etc. It discusses the effectiveness of the region growing technique applied on various medical images.
引用
收藏
页码:234 / 259
页数:26
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