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	Radiomics analysis potentially reduces over-diagnosis of prostate cancer with PSA levels of 4-10 ng/ml based on DWI data 会议论文 OAI收割 San Diego, California, United States, 2019-3-13 作者: Zhang, Shuaitong; Qi, Yafei; Wei, Jingwei; Niu, Jianxing; Gu, Dongsheng \| 收藏 \| 浏览/下载：30/0 \| 提交时间：2020/06/11 Prostate specific antigen Prostate cancer Over-diagnosis Radiomics Random forest
	Fault diagnosis and robust fault-tolerant control for linear over-actuated systems 期刊论文 OAI收割 Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 2016, 卷号: 230, 期号: 5, 页码: 832-844 作者: Zhou M(周萌); Qi JT(齐俊桐); Wang ZH(王振华); Shen Y(沈毅) 收藏 \| 浏览/下载：29/0 \| 提交时间：2016/04/30 Over-actuated systems fault diagnosis robust fault-tolerant control sparse optimization virtual actuator
	The application of adaptive enhancement algorithm based on gray entropy in mammary gland CR image (EI CONFERENCE) 会议论文 OAI收割 2012 2nd International Conference on Consumer Electronics, Communications and Networks, CECNet 2012, April 21, 2012 - April 23, 2012, Three Gorges, China Zhang M.-H.; Zhang Y.-Y. 收藏 \| 浏览/下载：34/0 \| 提交时间：2013/03/25 Mammary gland is composed entirely of soft tissue with approximate density therefore mammary gland CR medicine radiation image presents a low contrast and slight difference changes may be a manifestation of tumor so it is necessary to enhance mammary gland CR image to improve its visual quality in order to meet the demands of doctor's clinical diagnosis. However the general enhancement algorithms over enhance the contrast and noise due to image details lost aiming at the defects a mammary gland CR medicine image adaptive enhancement arithmetic based on image gray entropy is put forward. The arithmetic adapts dizzy image to magnify selected spatial frequency response in order to enhance the edge details of mammary gland CR images. It can adjust weighted factor K according to image gray characteristics namely pixel gray entropy. Experiments results demonstrate that mammary gland CR image enhanced by the algorithm has abundant details and high signal-to-noise ratio moreover CR image enhanced has good visual effect. So the method is effective and fit for enhancing CR medical radiation image edge details. 2012 IEEE.
	The research of digltal CR medicine image adapitive enhancement method (EI CONFERENCE) 会议论文 OAI收割 4th International Conference on Mechanical and Electrical Technology, ICMET 2012, July 24, 2012 - July 26, 2012, Kuala Lumpur, Malaysia Ming-Hui Z.; Yao-Yu Z. 收藏 \| 浏览/下载：66/0 \| 提交时间：2013/03/25 Digital CR medicine radiation image is in doctor's favor and has became medicine imaging technology new hot spot because of its high gray contrast powerful computer disposal function little radiation dosage non-film diagnosis different area consultation. But degradation of digital X-ray medical image such as low contrast and blurring during radiographic imaging caused by complexity of body tissue and effects of X-ray scattering and electrical noise etc. can worsen the results of analysis and diagnosis. So it is usually needed that CR medicine image is enhanced to improve its vision quality and easy to doctor's more accurate diagnosis. The general enhancement algorithms over enhancing the contrast and lose image details aiming at the defects an enhancement algorithm for CR image is proposed based on the ratio of deviation to mean of domain. The arithmetic enhance CR image edge details by adjusting factor K based on the ratio of deviation to mean of domain of CR image. Experiment results demonstrate that the algorithm enhances CR image detail and CR image enhanced has good visual effect the adaptive enhancement method is fit for CR medicine image. (2012) Trans Tech Publications Switzerland.
	Multi-focus image fusion algorithm based on adaptive PCNN and wavelet transform (EI CONFERENCE) 会议论文 OAI收割 International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Imaging Detectors and Applications, May 24, 2011 - May 26, 2011, Beijing, China Wu Z.-G.; Wang M.-J.; Han G.-L. 收藏 \| 浏览/下载：78/0 \| 提交时间：2013/03/25 Being an efficient method of information fusion image fusion has been used in many fields such as machine vision medical diagnosis military applications and remote sensing.In this paper Pulse Coupled Neural Network (PCNN) is introduced in this research field for its interesting properties in image processing including segmentation target recognition et al. and a novel algorithm based on PCNN and Wavelet Transform for Multi-focus image fusion is proposed. First the two original images are decomposed by wavelet transform. Then based on the PCNN a fusion rule in the Wavelet domain is given. This algorithm uses the wavelet coefficient in each frequency domain as the linking strength so that its value can be chosen adaptively. Wavelet coefficients map to the range of image gray-scale. The output threshold function attenuates to minimum gray over time. Then all pixels of image get the ignition. So the output of PCNN in each iteration time is ignition wavelet coefficients of threshold strength in different time. At this moment the sequences of ignition of wavelet coefficients represent ignition timing of each neuron. The ignition timing of PCNN in each neuron is mapped to corresponding image gray-scale range which is a picture of ignition timing mapping. Then it can judge the targets in the neuron are obvious features or not obvious. The fusion coefficients are decided by the compare-selection operator with the firing time gradient maps and the fusion image is reconstructed by wavelet inverse transform. Furthermore by this algorithm the threshold adjusting constant is estimated by appointed iteration number. Furthermore In order to sufficient reflect order of the firing time the threshold adjusting constant is estimated by appointed iteration number. So after the iteration achieved each of the wavelet coefficient is activated. In order to verify the effectiveness of proposed rules the experiments upon Multi-focus image are done. Moreover comparative results of evaluating fusion quality are listed. The experimental results show that the method can effectively enhance the edge details and improve the spatial resolution of the image. 2011 SPIE.
	Lossless wavelet compression on medical image (EI CONFERENCE) 会议论文 OAI收割 4th International Conference on Photonics and Imaging in Biology and Medicine, September 3, 2005 - September 6, 2005, Tianjin, China 作者: Liu H.; Liu H.; Liu H. 收藏 \| 浏览/下载：42/0 \| 提交时间：2013/03/25 An increasing number of medical imagery is created directly in digital form. Such as Clinical image Archiving and Communication Systems (PACS). as well as telemedicine networks require the storage and transmission of this huge amount of medical image data. Efficient compression of these data is crucial. Several lossless and lossy techniques for the compression of the data have been proposed. Lossless techniques allow exact reconstruction of the original imagery while lossy techniques aim to achieve high compression ratios by allowing some acceptable degradation in the image. Lossless compression does not degrade the image thus facilitating accurate diagnosis of course at the expense of higher bit rates i.e. lower compression ratios. Various methods both for lossy (irreversible) and lossless (reversible) image compression are proposed in the literature. The recent advances in the lossy compression techniques include different methods such as vector quantization wavelet coding neural networks and fractal coding. Although these methods can achieve high compression ratios (of the order 50:1 or even more) they do not allow reconstructing exactly the original version of the input data. Lossless compression techniques permit the perfect reconstruction of the original image but the achievable compression ratios are only of the order 2:1 up to 4:1. In our paper we use a kind of lifting scheme to generate truly loss-less non-linear integer-to-integer wavelet transforms. At the same time we exploit the coding algorithm producing an embedded code has the property that the bits in the bit stream are generated in order of importance so that all the low rate codes are included at the beginning of the bit stream. Typically the encoding process stops when the target bit rate is met. Similarly the decoder can interrupt the decoding process at any point in the bil stream and still reconstruct the image. Therefore a compression scheme generating an embedded code can start sending over the network the coarser version of the image first and continues with the progressive transmission of the refinement details. Experimental results show that our method can get a perfect performance in compression ratio and reconstructive image.