Contrast improvement of medical images using advanced fuzzy logic-based technique

2021 ◽  
pp. 229-257
Author(s):  
Dibya Jyoti Bora
Keyword(s):  
Fuzzy Logic ◽  
Medical Images

Edge Detection on Medical Images Using Intuitionistic Fuzzy Logic

2021 ◽  
pp. 236-246
Author(s):  
Nidhi Tripathi ◽  
Deepak Kumrawat ◽  
Venkata Keerthi Gottimukkala ◽  
S. Jeevaraj ◽  
W. Wilfred Godfrey
Keyword(s):  
Fuzzy Logic ◽  
Edge Detection ◽  
Medical Images ◽  
Intuitionistic Fuzzy ◽  
Intuitionistic Fuzzy Logic

scholarly journals Medical Images Enhanced by Using Fuzzy Logic Depending on Contrast Stretch Membership Function

2021 ◽  
Vol 14 (1) ◽  
pp. 368-375
Author(s):  
Rafid Ali ◽  
◽  
Asaad Abbas ◽  
Hazim Daway ◽  
◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Magnetic Resonance ◽  
Membership Function ◽  
Dynamic Range ◽  
Medical Images ◽  
Color Gamut ◽  
Order Error ◽  
X Ray ◽  
Average Value ◽  
Different Types

Medical images are often adversely affected by a lack of clarity due to the limited representation of the color gamut. In this research, three types of medical images microscopic, magnetic resonance and x-ray images were enhanced by using a Fuzzy Logic by Stretch Membership Function (FLSMF). The Stretch Membership Function increased the dynamic range for the compounds red, green and blue in the medical images which have a few ranges. The FLSMF algorithm was compared with other methods by calculating the entropy value, wavelet quality evaluator and lightness order error. The analysis of the results showed that the proposed method succeeded in enhancing the contrast of the different types of medical images where it had high average values for the entropy (6.95) and wavelet quality evaluator (0.08), and a small average value for the lightness order error (60.77).

scholarly journals A Multi Resolution Based Guided Filter Using Fuzzy Logic for X-Ray Medical Images

2014 ◽  
Vol 24 (4) ◽  
pp. 372-378
Author(s):  
Seung-Hyun Ko ◽  
Suresh Raj Pant ◽  
Joonwhoan Lee
Keyword(s):  
Fuzzy Logic ◽  
Medical Images ◽  
Guided Filter ◽  
X Ray

scholarly journals Biomedical Image Compression Techniques for Clinical Image Processing

2020 ◽  
Vol 16 (12) ◽  
pp. 133
Author(s):  
Abdul Khader Jilani Saudagar
Keyword(s):  
Image Processing ◽  
Fuzzy Logic ◽  
Image Compression ◽  
Image Coding ◽  
Medical Images ◽  
Focal Point ◽  
Clinical Image ◽  
Coding System ◽  
Quality Factors ◽  
Clinical Images

Image processing is widely used in the domain of biomedical engineering especially for compression of clinical images. Clinical diagnosis receives high importance which involves handling patient’s data more accurately and wisely when treating patients remotely. Many researchers proposed different methods for compression of medical images using Artificial Intelligence techniques. Developing efficient automated systems for compression of medical images in telemedicine is the focal point in this paper. Three major approaches were proposed here for medical image compression. They are image compression using neural network, fuzzy logic and neuro-fuzzy logic to preserve higher spectral representation to maintain finer edge information’s, and relational coding for inter band coefficients to achieve high compressions. The developed image coding model is evaluated over various quality factors. From the simulation results it is observed that the proposed image coding system can achieve efficient compression performance compared with existing block coding and JPEG coding approaches, even under resource constraint environments.

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