Detection of Nuclear Buds Based on Ellipse Fitting

2010 International Conference on Digital Image Computing: Techniques and Applications ◽

10.1109/dicta.2010.41 ◽

2010 ◽

Cited By ~ 3

Author(s):

Chao Zhang ◽

Changming Sun ◽

Tuan D. Pham ◽

Pascal Vallotton ◽

Michael Fenech

Keyword(s):

Ellipse Fitting

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Rotating High Frequency Injection and Ellipse Fitting Technique for Ringed-Pole Motor Sensorless Control

2020 Fifteenth International Conference on Ecological Vehicles and Renewable Energies (EVER) ◽

10.1109/ever48776.2020.9243045 ◽

2020 ◽

Author(s):

Ons Ben Abdallah ◽

Ahmed Masmoudi ◽

Matteo Berto ◽

Luigi Alberti ◽

Silverio Bolognani

Keyword(s):

High Frequency ◽

Sensorless Control ◽

Ellipse Fitting

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Subcycle Voltage Dip Classification Using Matrix Pencil Method With Ellipse Fitting Algorithm

IEEE Transactions on Industry Applications ◽

10.1109/tia.2014.2347455 ◽

2015 ◽

Vol 51 (2) ◽

pp. 1660-1668 ◽

Cited By ~ 11

Author(s):

Meng Hwee Chia ◽

Ashwin M. Khambadkone

Keyword(s):

Matrix Pencil ◽

Ellipse Fitting ◽

Voltage Dip ◽

Matrix Pencil Method ◽

Fitting Algorithm

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Connectivity-based error evaluation for ellipse fitting

2015 14th IAPR International Conference on Machine Vision Applications (MVA) ◽

10.1109/mva.2015.7153147 ◽

2015 ◽

Author(s):

Tomonari Masuzaki ◽

Yasuyuki Sugaya

Keyword(s):

Ellipse Fitting ◽

Error Evaluation

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Cell Segmentation Via Region-Based Ellipse Fitting

2018 25th IEEE International Conference on Image Processing (ICIP) ◽

10.1109/icip.2018.8451852 ◽

2018 ◽

Cited By ~ 2

Author(s):

Costas Panagiotakis ◽

Antonis A. Argyros

Keyword(s):

Cell Segmentation ◽

Ellipse Fitting

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Camera calibration using adaptive segmentation and ellipse fitting for localizing control points

2012 19th IEEE International Conference on Image Processing ◽

10.1109/icip.2012.6466865 ◽

2012 ◽

Cited By ~ 3

Author(s):

Charan D. Prakash ◽

Lina J. Karam

Keyword(s):

Camera Calibration ◽

Control Points ◽

Ellipse Fitting ◽

Adaptive Segmentation

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Accurate and fast two-step phase shifting algorithm based on principle component analysis and Lissajous ellipse fitting with random phase shift and no pre-filtering

Optics Express ◽

10.1364/oe.27.020047 ◽

2019 ◽

Vol 27 (14) ◽

pp. 20047 ◽

Cited By ~ 5

Author(s):

Yu Zhang ◽

Xiaobo Tian ◽

Rongguang Liang

Keyword(s):

Phase Shift ◽

Principle Component Analysis ◽

Random Phase ◽

Component Analysis ◽

Phase Shifting ◽

Ellipse Fitting ◽

Principle Component

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AN IMPROVED RANDOM WALK SEGMENTATION ON THE LUNG NODULES

International Journal of Biomathematics ◽

10.1142/s1793524513500435 ◽

2013 ◽

Vol 06 (06) ◽

pp. 1350043 ◽

Cited By ~ 1

Author(s):

LI GUO ◽

YUNTING ZHANG ◽

ZEWEI ZHANG ◽

DONGYUE LI ◽

YING LI

Keyword(s):

Random Walk ◽

Lung Nodule ◽

Texture Feature ◽

Ellipse Fitting ◽

Lung Nodule Detection ◽

Random Walk Algorithm ◽

Fitting Algorithm ◽

Nodule Detection ◽

Walk Algorithm ◽

Automatic Technique

In this paper, we proposed a semi-automatic technique with a marker indicating the target to locate and segment nodules. For the lung nodule detection, we develop a Gabor texture feature by FCM (Fuzzy C Means) segmentation. Given a marker indicating a rough location of the nodules, a decision process is followed by applying an ellipse fitting algorithm. From the ellipse mask, the foreground and background seeds for the random walk segmentation can be automatically obtained. Finally, the edge of the nodules is obtained by the random walk algorithm. The feasibility and effectiveness of the proposed method are evaluated with the various types of the nodules to identify the edges, so that it can be used to locate the nodule edge and its growth rate.

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