title: Curvelet initialized level set cell segmentation for touching cells in low contrast images.
abstract: Cell segmentation is an important element of automatic cell analysis. This paper proposes a method to extract the cell nuclei and the cell boundaries of touching cells in low contrast images. First, the contrast of the low contrast cell images is improved by a combination of multiscale top hat filter and h-maxima. Then, a curvelet initialized level set method has been proposed to detect the cell nuclei and the boundaries. The image enhancement results have been verified using PSNR (Peak Signal to noise ratio) and the segmentation results have been verified using accuracy, sensitivity and precision metrics. The results show improved values of the performance metrics with the proposed method.
authors.affiliation: Department of Electrical Engineering, Indian Institute of Technology, Ropar, India. Electronic address: sarabpreetk@iitrpr.ac.in.
authors.forename: Sarabpreet
authors.initials: S
authors.lastname: Kaur
authors.affiliation: Department of Electrical Engineering, Indian Institute of Technology, Ropar, India. Electronic address: jsahambi@iitrpr.ac.in.
authors.forename: J S
authors.initials: JS
authors.lastname: Sahambi
mesh_terms: D000465:Algorithms; D002462:Cell Membrane / Q000648:ultrastructure*; D002467:Cell Nucleus / Q000648:ultrastructure*; D058948:Cell Tracking / Q000379:methods*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D008853:Microscopy / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D059629:Signal-To-Noise Ratio; D002583:Uterine Cervical Neoplasms / Q000000981:diagnostic imaging*; D058067:Wavelet Analysis
keywords: Cell segmentation; Curvelets; Level sets; Multiscale top hat transform; h-maxima