2020
DOI: 10.1002/ima.22455
|View full text |Cite
|
Sign up to set email alerts
|

Modified Global Flower Pollination Algorithm‐based image fusion for medical diagnosis using computed tomography and magnetic resonance imaging

Abstract: Recently, the computed tomography (CT) and magnetic resonance imaging (MRI) medical image fusion have turned into a challenging issue in the medical field. The optimal fused image is a significant component to detect the disease easily. In this research, we propose an iterative optimization approach for CT and MRI image fusion. Initially, the CT and MRI image fusion is subjected to a multilabel optimization problem. The main aim is to minimize the data and smoothness cost during image fusion. To optimize the f… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

0
5
0

Year Published

2021
2021
2024
2024

Publication Types

Select...
4
2
1

Relationship

0
7

Authors

Journals

citations
Cited by 7 publications
(5 citation statements)
references
References 28 publications
0
5
0
Order By: Relevance
“…,  represents the step size adjustment factor for the search process and parameter L represents pollination intensity, which follows the Levy distribution and its expression is as follows [34]:…”
Section: Scale Adaptive Adjustment Methods Of Tracking Framementioning
confidence: 99%
See 1 more Smart Citation
“…,  represents the step size adjustment factor for the search process and parameter L represents pollination intensity, which follows the Levy distribution and its expression is as follows [34]:…”
Section: Scale Adaptive Adjustment Methods Of Tracking Framementioning
confidence: 99%
“…where ) (  represents the standard gamma function, and  takes the value 1.5 [34]. 5) Calculation of the optimal solution and fitness value of the updated population.…”
Section: Scale Adaptive Adjustment Methods Of Tracking Framementioning
confidence: 99%
“…Although some FPA algorithm research has achieved good results in most optimization problems [14][15][16], there are still problems such as easy to fall into local optimum [17][18], the low search precision, and insufficient development ability [19]. To solve more optimization problems, many scholars improve the performance of FPA mainly from 5 aspects, the improvement of the initial population [20][21], the improvement in population diversity [22][23], the improvement in parameter settings [24][25], the improvement in search capabilities [26][27] and designing hybrid algorithms [28][29].…”
Section: Related Workmentioning
confidence: 99%
“…Color and shape alteration of the nuclei and cytoplasm can implicate the occurrence of Papilloma virus that causes cervical cancer [ 3 , 4 ]. Manual Pap smear testing is slow and error-prone procedure and requires pathology experts [ 5 , 6 ]. It was found that a lot of inconsistencies from the manual test can compromise the validity the Pap smear process [ 7 ].…”
Section: Introductionmentioning
confidence: 99%