Measurement of smaller colon polyp in CT colonography images using morphological image processing

Manjunath, K.; Siddalingaswamy, P. C.; Prabhu, K. Gopalakrishna

doi:10.1007/s11548-017-1615-4

Cited by 5 publications

(2 citation statements)

References 24 publications

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“…Without this, the same image looks different in different display systems (Kagadis et al, 2013) which may lead to wrong interpretation. A prototype software has been developed that has the basic features of medical image processing applications (Manjunath et al, 2017). In addition to testing the images in the prototype software, the images were checked syngoFastView from SIEMENS (Siemens, 2019), DicomViewer from Philips (Philips, 2020) and MITK software from dkfz (GCRF, 2020), Germany for the viewing the images of the patient.…”

Section: E Data Analysis and Processing E1 Data Analysismentioning

confidence: 99%

A Systematic Approach of Data Collection and Analysis in Medical Imaging Research

Manjunath

Manuel²,

Hegde

et al. 2021

Asian Pac J Cancer Prev

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Section: E Data Analysis and Processing E1 Data Analysismentioning

confidence: 99%

A Systematic Approach of Data Collection and Analysis in Medical Imaging Research

Manjunath

Manuel²,

Hegde

et al. 2021

Asian Pac J Cancer Prev

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“…The .NET framework supports the cryptography library. The DICOM image validation and the creation of DRR image functions have been considered from (Manjunath, 2017).…”

Section: Introductionmentioning

confidence: 99%

Data Integrity of Radiology Images Over an Insecure Network Using AES Technique

Prabhu

Manjunath

Rajarama³

et al. 2021

Asian Pac J Cancer Prev

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Background: While transmitting the medical images in radiology information systems the adversary effect can break the CIA (Confidentiality, Integrity, and Availability) triads of information security. The objective of the study was to transmit the complete set of image objects in a dataset without data integrity violation. Methods: In this paper a hybrid cryptographic technique which combines the prime details from the patient dataset (stack of axial 2D images) and the Advanced Encryption Standard (AES) method has been proposed. The steps include a) Creating an artificial X-ray image (DRR) from the 3D volume, b) dividing the DRR image in x and y directions equally into four regions, c) applying the zig-zag pattern to each quadrant, and d) encryption of each quadrant with block cipher mode using the AES algorithm. After dataset transmission the DRR image was regenerated at the receiver and compared each of the deciphered blocks (transmitted ones) using the histogram technique. Results: The technique was tested on CT and MRI scans of sixty datasets. The image injection techniques, such as adding and deleting an image from the dataset and modifying the image pixels, were tested. The results were validated statistically using mean square error and histogram matching techniques. Conclusion: The combination of the DRR and the AES technique has ensured the secured transmission of the entire dataset and not an individual image.

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Secured Transmission of Medical Images in Radiology Using AES Technique

Prabhu

Manjunath

2019

Computer Aided Intervention and Diagnostics in Clinical and Medical Images

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Measurement of smaller colon polyp in CT colonography images using morphological image processing

Cited by 5 publications

References 24 publications

A Systematic Approach of Data Collection and Analysis in Medical Imaging Research

A Systematic Approach of Data Collection and Analysis in Medical Imaging Research

Data Integrity of Radiology Images Over an Insecure Network Using AES Technique

Secured Transmission of Medical Images in Radiology Using AES Technique

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