Radionuclide Colloid ^(32)P Used for the Treatment of Stage II Lung Cancer by Video Enhanced Minimal Access Muscle Sparing Thoracotomy

Objective: To study the feasibility of radionuclide colloid 32P used for the treatment of stage II lung cancer by video enhanced minimal access muscle sparing thoracotomy (VEMAST). Methods: Video assisted thoracoscopic surgery (VATS) was carried out under general anesthesia. A double lumen endobronchial tube was intubated into trachea. One lung ventilation of the healthy side was done during operation. An incision of 8–10 cm long was made along the 4th or 5th intercostals. The lobectomy could be performed under VATS. Radionuclide colloid 32P was injected locally into the area where surgical cleaning of lymph node around was considered to be unsatisfactory or desection of the tumor was not completed. Results: The operation with VEMAST was successful in 29 patients. A conventional lobectomy by thoracotomy had to be done due to unusual bleeding from the pulmonary artery involved during VEMAST in one case and the procedure was interrupted because the pulmonary artery cloud not be separated from the tumor in another patient. There was no dead case or the patient who had any severe complication or adverse response to the radiant. Conclusion: Radionuclide therapy was performed to the treatment of stage II lung cancer with VEMAST in case that surgical resection was considered not to be satisfactory. Minithoractomy assisted with VATS lobectomy and radionuclide colloid 32P therapy is a safe and e?ective technique for some selected stage II lung cancer.

Video Enhancement Network Based on CNN and Transformer

To enhance the video quality after encoding and decoding in video compression,a video quality enhancement framework is pro-posed based on local and non-local priors in this paper.Low-level features are first extracted through a single convolution layer and then pro-cessed by several conv-tran blocks(CTB)to extract high-level features,which are ultimately transformed into a residual image.The final re-constructed video frame is obtained by performing an element-wise addition of the residual image and the original lossy video frame.Experi-ments show that the proposed Conv-Tran Network(CTN)model effectively recovers the quality loss caused by Versatile Video Coding(VVC)and further improves VVC's performance.

COMBINING SCENE MODEL AND FUSION FOR NIGHT VIDEO ENHANCEMENT

This paper presents a video context enhancement method for night surveillance. The basic idea is to extract and fuse the meaningful information of video sequence captured from a fixed camera under different illuminations. A unique characteristic of the algorithm is to separate the image context into two classes and estimate them in different ways. One class contains basic surrounding scene in- formation and scene model, which is obtained via background modeling and object tracking in daytime video sequence. The other class is extracted from nighttime video, including frequently moving region, high illumination region and high gradient region. The scene model and pixel-wise difference method are used to segment the three regions. A shift-invariant discrete wavelet based image fusion technique is used to integral all those context information in the final result. Experiment results demonstrate that the proposed approach can provide much more details and meaningful information for nighttime video.

An efficient algorithm and FPGA implementation of video luminance transient improvement

In this paper, a high-performance and low-complexity luminance transient improvement （LTI） algorithm is proposed and efficiently implemented on field programmable gate army （FPGA） devices, which can be widely used to enhance the sharpness of digital video. The proposed algorithm generates the cor- rection signal by using the difference of the outputs of two Gaussian filters with different variances, and then modulates the correction signal adaptively according to the local contrast information of video frames. A 2-D min/max nonlinear filter is employed to suppress overshoots around edges. The proposed algorithm is thoroughly confirmed by experiments and compared with other algorithms on irrkages, which produces steeper edges and better visual quality while suppressing noise and artifacts. And the hardware architecture suitable for FPGA implementation is optimized based on the property of the algorithm and proves to be effective and efficient in many respects, such as resource consumption, performance and reconfigura- bility. The specific implementation details on both Xilinx and Ahera FPGA devices are also described in this paper.