中国科学院机构知识库网格系统: 检索

Accurate Lung Nodule Segmentation With Detailed Representation Transfer and Soft Mask Supervision 期刊论文 OAI收割
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 页码: 13
作者: Wang, Changwei; Xu, Rongtao; Xu, Shibiao; Meng, Weiliang; Xiao, Jun

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收藏 | 浏览/下载：13/0 | 提交时间：2023/12/21

Detailed representation transfer lung nodules segmentation medical images segmentation soft mask

Uncertainty Quantification in Medical Image Segmentation 会议论文 OAI收割
Chengdu, China, December 11-14, 2020
作者: Li HX(李海星); Luo HB(罗海波)

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收藏 | 浏览/下载：28/0 | 提交时间：2021/11/21

medical images uncertainty quantification segmentation prostate MRI image

Local difference-based active contour model for medical image segmentation and bias correction 期刊论文 OAI收割
IET Image Processing, 2019, 卷号: 13, 期号: 10, 页码: 1755-1762
作者: Niu, Yuefeng; Cao, Jianzhong

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收藏 | 浏览/下载：71/0 | 提交时间：2019/09/25

image segmentation medical image processing two-phase model medical images LBDE model precise segmentation results comparative models local difference-based active contour model medical image segmentation bias correction local bias field difference estimation model smooth orthogonal basis functions clustering criterion function measured image local region accurate segmentation results level set evolution process

Local difference-based active contour model for medical image segmentation and bias correction 期刊论文 OAI收割
IET IMAGE PROCESSING, 2019, 卷号: 13, 期号: 10, 页码: 1755-1762
作者: Niu, Yuefeng; Cao, Jianzhong

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收藏 | 浏览/下载：26/0 | 提交时间：2020/06/05

image segmentation medical image processing two-phase model medical images LBDE model precise segmentation results comparative models local difference-based active contour model medical image segmentation bias correction local bias field difference estimation model smooth orthogonal basis functions clustering criterion function measured image local region accurate segmentation results level set evolution process

A case-oriented web-based training system for breast cancer diagnosis 期刊论文 OAI收割
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2018, 卷号: 156, 页码: 73-83
作者: Huang, Qinghua; Huang, Xianhai; Liu, Longzhong; Lin, Yidi; Long, Xingzhang

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收藏 | 浏览/下载：39/0 | 提交时间：2018/12/12

Breast Ultrasound Images Medical Database Web-based Training Feature Scoring Bi-rads Computer-aided Diagnosis

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.

Application of adaptive enhancement means in head and neck CR image (EI CONFERENCE) 会议论文 OAI收割
2012 3rd International Conference on Information Technology for Manufacturing Systems, ITMS 2012, September 8, 2012 - September 9, 2012, Qingdao, China
Zhang M.-H.; Zhang Y.-Y.

收藏 | 浏览/下载：35/0 | 提交时间：2013/03/25

Digital CR of head and neck overcomes the disadvantage of regular X-ray radiography which can not reveal bone and soft tissue position deficiency in one exposing and reduces the Xray radiation dose. Meanwhile various factors cause the decline of image quality and images must be enhanced in order to meet demands of doctor's clinical diagnosis. The general enhancement algorithms don't consider body's structure differences and density characteristics. A new adaptive CR enhancement algorithm was proposed in this article and head and neck CR images were processed with this method and compared with linear unsharp masking method. The experiment proves that the details of CR image enhanced were abundant and enhanced CR image had good visual effect SNR was high as well as detail variance /background variance (DV/BV) indicating that this algorithm is suitable for head and neck CR medical images. (2012) Trans Tech Publications Switzerland.

A parallel algorithm for medical images registration based on B-splines (EI CONFERENCE) 会议论文 OAI收割
4th International Congress on Image and Signal Processing, CISP 2011, October 15, 2011 - October 17, 2011, Shanghai, China
作者: Zhang T.

收藏 | 浏览/下载：26/0 | 提交时间：2013/03/25

Cubic B-splines is widely applied in non-rigid registration because of its approximation performance and fast computational characteristics. However a small scale non-rigid deformation is needed to characterize by a large number of control points. Moreover an iterative optimization strategy of the non-rigid registration algorithm and the normalized mutual information (NMI) cost a great quantity calculation. So the process of the non-rigid registration is slowed by calculations of NMI in a iterative optimization strategy. In this paper a parallel optimization algorithm based on cubic B-splines functions is proposed to parallelize the optimization algorithm of the nonrigid registration and the calculations of normalize mutual information. In practice a fast algorithm of cubic B-splines is used and the control points are only distributed on the targets. Experiments show that the use of the fast algorithm and the parallel optimization strategy improves the non-rigid registration process of medical images. 2011 IEEE.

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：75/0 | 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.

Experiment of coherent scatter imaging based digital radiography device (EI CONFERENCE) 会议论文 OAI收割
2011 IEEE International Conference on Computer Science and Automation Engineering, CSAE 2011, June 10, 2011 - June 12, 2011, Shanghai, China
作者: Li B.; Wang K.; Liu J.; Liu J.; Liu J.

收藏 | 浏览/下载：22/0 | 提交时间：2013/03/25

This paper introduces a new imaging method for X-ray coherent scatter based on a new medical digital radiography device. An experimental equipment was set up and the scatter images obtained with it. The scatter images are made of some circles with the same center. With image processing the energy distribution curve extracted from coherent scatter images. The experiment results show that this method is reasonable and feasible. The study will have wide foreground of application. 2011 IEEE.