The effect of contrast enhancement techniques on mutual information based image registration

Atlı, İbrahim; Saracoğlu, Ahmet; Gedik, O. Serdar

doi:10.1109/siu.2017.7960558

Cited by 2 publications

(2 citation statements)

References 24 publications

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“…Digital image enhancement is a very vast field and it is quite complex also due to the usage of mathematical calculations. The process of image enhancements is initiated by an input image which is further processed by the computer by using some calculations and on the basis of these calculations the modifications are done in the image automatically [3]. The results obtained after enhancement can be displayed on the monitor or can also be kept for the purpose of future use.…”

Section: Introductionmentioning

confidence: 99%

Region of Interest based Contrast Enhancement Techniques for CT Image

Kaur¹

2018

IJRASET

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Medical images are used for decision making purpose by the physicians to recognize the disease by which the patient is suffering. Thus to lead the highly reliable results, it is mandatory that the image should be more qualitative and informative. In order to make an image more qualitative, the image enhancement technique is applied to it. Image enhancement is such a vast field and covers a large number of enhancing mechanisms under it. This study develops a medical image contrast enhancement technique by applying multi filters, curvelet transformation and un-sharp masking. For Multi Filtration, the Kuwahara filter and Gaussian filter is used in this. Along with this the ROI is applied to detect the infected areas or noise from the image. The implementation results show that the final enhanced image is quite qualitative in comparison to the initially input image in terms of Bit Error Rate, Mean Square Error, Standard Deviation, Peak Signal to Noise Ratio, Entropy, Contrast to Noise Ratio etc.

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Section: Introductionmentioning

confidence: 99%

Region of Interest based Contrast Enhancement Techniques for CT Image

Kaur¹

2018

IJRASET

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“…Woo et al [ 14 ] demonstrated a multimodal Registration via Mutual Information Incorporating Geometric and Spatial Context. Atli et al [ 15 ] combined contrast enhancement techniques with MI-based image registration. Legg et al [ 16 ] used the feature neighbourhood mutual information for multimodal image registration.…”

Section: Introductionmentioning

confidence: 99%

Large-Deformation Image Registration of CT-TEE for Surgical Navigation of Congenital Heart Disease

Gou

Chen

et al. 2018

Computational and Mathematical Methods in Medicine

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The surgical treatment of congenital heart disease requires navigational assistance with transesophageal echocardiography (TEE); however, TEE images are often difficult to interpret and provide very limited anatomical information. Registering preoperative CT images to intraoperative TEE images provides surgeons with richer and more useful anatomical information. Yet, CT and TEE images differ substantially in terms of scale and geometry. In the present research, we propose a novel method for the registration of CT and TEE images for navigation during surgical repair of large defects in patients with congenital heart disease. Valve data was used for the coarse registration to determine the basic location. This was followed by the use of an enhanced probability model map to overcome gray-level differences between the two imaging modalities. Finally, the rapid optimization of mutual information was achieved by migrating parameters. This method was tested on a dataset of 240 images from 12 infant, children (≤ 3 years old), and adult patients with congenital heart disease. Compared to the “bronze standard” registration, the proposed method was more accurate with an average Dice coefficient of 0.91 and an average root mean square of target registration error of 1.2655 mm.

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The effect of contrast enhancement techniques on mutual information based image registration

Cited by 2 publications

References 24 publications

Region of Interest based Contrast Enhancement Techniques for CT Image

Region of Interest based Contrast Enhancement Techniques for CT Image

Large-Deformation Image Registration of CT-TEE for Surgical Navigation of Congenital Heart Disease

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