Ranu Gupta^1,3,*, Rahul Pachauri^2,3, Ashutosh Kumar Singh^1,4

Molecular & Cellular Biomechanics, Vol.15, No.2, pp. 63-83, 2018, DOI: 10.3970/mcb.2018.00114

Abstract Various chaos-based image encryption schemes have been proposed in last few years. The proposed image encryption method uses chaotic map. The encryption is done by using 256 bit long external secret key. The initial condition for the chaotic mapping is evaluated by the use of external secret key along with the mapping function. Besides that, the proposed method is made more robust by applying multiple operations to the pixels of the image depending on the outcome of the calculation of the logistic map. Moreover, block shuffling of the image and modifying the secret key after encryption of each row is… More >

Maoyang Zou^1,2, Jinrong Hu², Huan Zhang², Xi Wu², Jia He², Zhijie Xu³, Yong Zhong^1,*

CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 511-525, 2019, DOI:10.32604/cmc.2019.05912

Abstract For image-guided radiation therapy, radiosurgery, minimally invasive surgery, endoscopy and interventional radiology, one of the important techniques is medical image registration. In our study, we propose a learning-based approach named “FIP-CNNF” for rigid registration of medical image. Firstly, the pixel-level interest points are computed by the full convolution network (FCN) with self-supervise. Secondly, feature detection, descriptor and matching are trained by convolution neural network (CNN). Thirdly, random sample consensus (Ransac) is used to filter outliers, and the transformation parameters are found with the most inliers by iteratively fitting transforms. In addition, we propose “TrFIP-CNNF” which uses transfer learning and fine-tuning… More >

Xingxing Xiao¹, Yang^1,*, Rui Li², Weiming Zhang³

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 101-115, 2019, DOI:10.32604/cmc.2019.05293

Abstract The medical industry develops rapidly as science and technology advance. People benefit from medical resource sharing, but suffer from privacy leaks at the same time. In order to protect patients’ privacy and improve quality of medical images, a novel reversible data hiding (RDH) scheme based on lesion extraction and with contrast enhancement is proposed. Furthermore, the proposed scheme can enhance the contrast of medial image's lesion area directly and embed high-capacity privacy data reversibly. Different from previous segmentation methods, this scheme first adopts distance regularized level set evolution (DRLSE) to extract lesion and targets at the lesion area accurately for… More >

J.B. Alford¹, D.C. Simkins¹, R.A. Rembert¹, L. Hoyte, MD²

CMES-Computer Modeling in Engineering & Sciences, Vol.98, No.2, pp. 129-149, 2014, DOI:10.3970/cmes.2014.098.129

Abstract Mechanical deformation of tissues in the female pelvic floor is believed to be central to understanding a number of important aspects of women’s health, particularly pelvic floor dysfunction. A 2008 study of US women reported the prevalence of pelvic floor disorders in the 20 and 39 years range as 9.7% with the prevalence increasing with age until it reaches roughly 50% in the 80 and older age group [Nygaard, Barber, Burgio, and et al (2008)]. Clinical observation indicates a strong correlation between problems such as pelvic organ prolapse/urinary incontinence and vaginal childbirth. It is thought that childbirth parameters like fetal… More >

Jialing Liu¹, Jingbing Li^1,2,*, Yenwei Chen³, Xiangxi Zou¹, Jieren Cheng^1,2, Yanlin Liu¹, Uzair Aslam Bhatti^1,2

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 363-378, 2019, DOI:10.32604/cmc.2019.06037

Abstract Remote medical diagnosis can be realized by using the Internet, but when transmitting medical images of patients through the Internet, personal information of patients may be leaked. Aim at the security of medical information system and the protection of medical images, a novel robust zero-watermarking based on SIFT-DCT (Scale Invariant Feature Transform-Discrete Cosine Transform) for medical images in the encrypted domain is proposed. Firstly, the original medical image is encrypted in transform domain based on Logistic chaotic sequence to enhance the concealment of original medical images. Then, the SIFT-DCT is used to extract the feature sequences of encrypted medical images.… More >