The track of medical imaging has witnessed several advancements in the last years. Several medical imaging modalities have appeared in the last decades including X-ray, Computed Tomography (CT), Magnetic Resonance (MR), Positron Emission Tomography (PET), Single-Photon Emission Computed Tomography (SPECT) and ultrasound imaging. Generally, medical images are used for the diagnosis purpose. Each type of acquired images has some merits and limitations. To maximize medical images utilization for the purpose of diagnosis, medical imaging fusion trend has appeared as a hot research field. Different medical imaging modalities are fused to obtain new images with complementary information. This paper presents a survey study of medical imaging modalities and their characteristics. In addition, different medical image fusion approaches and their appropriate quality metrics are presented. The main aim of this comprehensive survey analysis is to contribute in the advancement of medical image approaches that can help for better diagnosis of different diseases.

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A Comprehensive Survey Analysis for Present Solutions of Medical Image Fusion and Future Directions

After analyzing some fusion rules based on wavelet transform and their effects,this paper presents a new method of image fusion.The test shows that this method can hold the information of the original images and enhance their detail information.

An Image Fusion Algorithm Using Wavelet Transform

Combining Gabor energy with equilibrium optimizer algorithm for multi-modality medical image fusion

Naturally, to analyze an image accurately, all the similar objects within it should be separated to pay attention to the most important object for reaching more details and hence achieving better accuracy. Therefore, multilevel thresholding is an indispensable image processing technique in the field of image segmentation and is employed widely to separate those similar objects. However, with increasing thresholds, the existing image segmentation techniques might suffer from exponentially-grown computational cost and low accuracy due to local optima shortage. Therefore, in this paper, a new image segmentation algorithm based on the improved marine predators algorithm (MPA) is proposed. MPA is improved using a strategy to find a number of the worst solutions within the population then tries to search for other better ones for those solutions by moving them gradually towards the best solutions to avoid accelerating to local optima and randomly within the search space based on a certain probability. In addition, this number of the worst solutions is increased with the iteration. This strategy is known as the linearly increased worst solutions improvement strategy (LIS). Also, we suggested that apply the ranking strategy based on a novel updating scheme, namely ranking-based updating strategy (RUS), on the solutions that could find better solutions in the last number iterations, perIter, in the hope of finding better solutions near it. RUS updates the particles/solutions which could not find better solutions than the best-local one in a number of consecutive iterations, with those that are generated based on a novel updating strategy. LIS is integrated with MPA to produce a new segmentation meta-heuristic algorithm abbreviated as MPALS. Also, MPALS and RUS are combined to tackle ISP in a strong variant abbreviated as HMPA for overcoming the image segmentation problem. The two proposed algorithms are validated on 14 test images and compared with seven state-of-the-arts meta-heuristic algorithms. The experimental results show the effectiveness of HMPA with increasing the threshold levels compared to the seven state-of-the-arts algorithms when segmenting an image, while their performance is roughly the same for the image with a small threshold level.

https://link.springer.com/content/pdf/10.1007/s10462-021-10086-0.pdf

Hybrid marine predators algorithm for image segmentation: analysis and validations

Joint sparse model with coupled dictionary for medical image fusion

Many types of medical images must be fused, as single‐modality medical images can only provide limited information due to the imaging principles and the complexity of human organ structures. In this paper, a multimodal medical image fusion method that combines the advantages of nonsubsampling contourlet transform (NSCT) and fuzzy entropy is proposed to provide a basis for clinical diagnosis and improve the accuracy of target recognition and the quality of fused images. An image is initially decomposed into low‐ and high‐frequency subbands through NSCT. The corresponding fusion rules are adopted in accordance with the different characteristics of the low‐ and high‐frequency components. The membership degree of low‐frequency coefficients is calculated. The fuzzy entropy is also computed and subsequently used to guide the fusion of coefficients to preserve image details. High‐frequency components are fused by maximizing the regional energy. The final fused image is obtained by inverse transformation. Experimental results show that the proposed method achieves good fusion effect based on the subjective visual effect and objective evaluation criteria. This method can also obtain high average gradient, SD, and edge preservation and effectively retain the details of the fused image. The results of the proposed algorithm can provide effective reference for doctors to assess patient condition.

Improving medical image fusion method using fuzzy entropy and nonsubsampling contourlet transform

Machine vision-based network monitoring system for solar-blind ultraviolet signal

The utility model discloses a novel pipeline inner wall spraying robot. Including a housing, side plates are fixedly connected to the two ends of the outer wall of one side of the bottom of the shell.One side of one side plate is fixedly connected with a rotating motor; u-shaped frames are fixedly connected to the outer walls of the two ends of the middle position of the bottom of the shell. Anda first walking gear is arranged on the inner wall of the opposite side of one U-shaped frame, a second walking gear is arranged on the inner wall of the opposite side of the other U-shaped frame, andone side of the second walking gear is fixedly connected with a rotating shaft rotationally connected with the outer wall of one side of the other side plate. The stability of the whole shell in themoving process in the pipeline is kept, paint in the liquid storage cavity is pumped out through the liquid pump and the liquid pumping pipe and sprayed out through the corrugated pipe, the spraying pipe and the spraying head, the spraying pipe is driven by the forward and reverse rotation motor to rotate in a reciprocating mode, and rotary spraying operation can be conveniently conducted on the inner wall of the pipeline.

Lin Qinyong

Papers

Improving medical image fusion method using fuzzy entropy and nonsubsampling contourlet transform

Machine vision-based network monitoring system for solar-blind ultraviolet signal

Novel pipeline inner wall spraying robot