Image Perception

Euishin   Edmund   Kim

[1] 
Saba T, Rehman A, Mehmood Z, Kolivand H, Sharif M. Image enhancement and segmentation techniques for detection of knee joint diseases: a survey. Curr Med Imaging  2018; 15(5): 704-15.
[2] 
Bokhari STF, Sharif M, Yasmin M, Fernandes SL. Fundus image segmentation and feature extraction for the detection of glaucoma: a new approach. Curr Med Imaging  2018; 14(1): 77-87.
[3] 
Naqi SM, Sharif M, Yasmin M, Fernandes SL. Lung nodule detection using polygon approximation and hybrid features from CT images. Curr Med Imaging  2018; 14(1): 108-17.
[4] 
Naqi SM, Sharif M. Recent developments in computer aided diagnosis for lung nodule detection from CT images: a review. Curr Med Imaging  2017; 13(1): 3-19.
[5] 
El-Regaily SA, Salem MA, Aziz MHA, Roushdy MI. Survey of computer aided detection systems for lung cancer in computed tomography. Curr Med Imaging  2018; 14(1): 3-18.
[6] 
Fernandes SL, Bala JG. A novel decision support for composite sketch matching using fusion of probabilistic neural network and dictionary matching. Curr Med Imaging  2017; 13(2): 176-84.
[7] 
Song G, Han J, Zhao Y, Wang Z, Du H. A review on medical image registration as an optimization problem. Curr Med Imaging  2017; 13(3): 274-83.
[8] 
Thakur N, Juneja M. Clustering based approach for segmentation of optic cup and optic disc for detection of glaucoma. Curr Med Imaging  2017; 13(1): 99-105.
[9] 
Rajan SP, Kavitha V. Diagnosis of cardiovascular diseases using retinal images through vessel segmentation graph.  Curr Med Imaging  13(4): 454-9.
[10] 
Garg G, Juneja M. A survey of prostate segmentation techniques in different imaging modalities. Curr Med Imaging  2018; 14(1): 19-46.

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Call for Papers in Thematic Issues

Submission closes on : 01 August, 2024

Intelligent Information Retrieval for Multispectral and Hyperspectral Imaging

Multispectral and hyperspectral imaging is an interdisciplinary research area, widely focuses on spectral, spatial, and temporal data. It offers a plethora of opportunities to efficiently analyze the vast area of the earth's surface. However, there are numerous factors such as dimensionality and size of the hyperspectral data, lesser training samples, ...read more

Guest Editor(s): Fadi Al-Turjman

Submission closes on : 18 May, 2024

Machine and Deep Learning in Medical Image Diagnosis

Medical Image Processing regards a set of methodologies that have been developed over recent years with the purpose of improving medical image quality, improving medical data visualization, understanding, and assisting medical diagnosis, and so on. The application of machine and deep learning methods in sensing and imaging can potentially have ...read more

Guest Editor(s): Jianqiao Fang

Submission closes on : 03 September, 2024

Quantum Machine Learning for Medical Data and Imaging

Quantum computing has promised a significant speedup in certain computationally intensive tasks that are intractable on classical computers. Researchers in quantum machine learning, such as those working in computer vision, image processing, biomedical analysis, and related topics, may play an important role in comprehending and working on complicated medical data, ...read more

Guest Editor(s): Deepak Gupta

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DOI https://dx.doi.org/10.2174/1573405615999190828153900	Print ISSN 1573-4056
Publisher Name Bentham Science Publisher	Online ISSN 1875-6603

Current Medical Imaging