In order to enhance cone-beam computed tomography (CBCT) image information and improve the registration accuracy for image-guided radiation therapy, we propose a super-resolution (SR) image enhancement method. This method uses super-resolution techniques to pre-process the CBCT prior to registration. Three rigid registration methods (rigid transformation, affine transformation, and similarity transformation) and a deep learning deformed registration (DLDR) method with and without SR were compared. The five evaluation indices, the mean squared error (MSE), mutual information, Pearson correlation coefficient (PCC), structural similarity index (SSIM), and PCC + SSIM, were used to validate the results of registration with SR. Moreover, the proposed method SR-DLDR was also compared with the VoxelMorph (VM) method. In rigid registration with SR, the registration accuracy improved by up to 6% in the PCC metric. In DLDR with SR, the registration accuracy was improved by up to 5% in PCC + SSIM. When taking the MSE as the loss function, the accuracy of SR-DLDR is equivalent to that of the VM method. In addition, when taking the SSIM as the loss function, the registration accuracy of SR-DLDR is 6% higher than that of VM. SR is a feasible method to be used in medical image registration for planning CT (pCT) and CBCT. The experimental results show that the SR algorithm can improve the accuracy and efficiency of CBCT image alignment regardless of which alignment algorithm is used.
Citation: Liwei Deng, Yuanzhi Zhang, Jingjing Qi, Sijuan Huang, Xin Yang, Jing Wang. Enhancement of cone beam CT image registration by super-resolution pre-processing algorithm[J]. Mathematical Biosciences and Engineering, 2023, 20(3): 4403-4420. doi: 10.3934/mbe.2023204
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In order to enhance cone-beam computed tomography (CBCT) image information and improve the registration accuracy for image-guided radiation therapy, we propose a super-resolution (SR) image enhancement method. This method uses super-resolution techniques to pre-process the CBCT prior to registration. Three rigid registration methods (rigid transformation, affine transformation, and similarity transformation) and a deep learning deformed registration (DLDR) method with and without SR were compared. The five evaluation indices, the mean squared error (MSE), mutual information, Pearson correlation coefficient (PCC), structural similarity index (SSIM), and PCC + SSIM, were used to validate the results of registration with SR. Moreover, the proposed method SR-DLDR was also compared with the VoxelMorph (VM) method. In rigid registration with SR, the registration accuracy improved by up to 6% in the PCC metric. In DLDR with SR, the registration accuracy was improved by up to 5% in PCC + SSIM. When taking the MSE as the loss function, the accuracy of SR-DLDR is equivalent to that of the VM method. In addition, when taking the SSIM as the loss function, the registration accuracy of SR-DLDR is 6% higher than that of VM. SR is a feasible method to be used in medical image registration for planning CT (pCT) and CBCT. The experimental results show that the SR algorithm can improve the accuracy and efficiency of CBCT image alignment regardless of which alignment algorithm is used.
Topological indices have become an important research topic associated with the study of their mathematical and computational properties and, fundamentally, for their multiple applications to various areas of knowledge (see, e.g., [1,2,3]). Within the study of mathematical properties, we will contribute to the study of inequalities and optimization problems associated with topological indices. Our main goals are the Sombor indices, introduced by Gutman in [4].
In what follows, will be a finite undirected graph, and we will assume that each vertex has at least a neighbor. We denote by the degree of the vertex , i.e., the number of neighbors of . We denote by the edge joining the vertices and (or and ). For each graph , its Sombor index is
In the same paper is also defined the reduced Sombor index by
In [5] it is shown that these indices have a good predictive potential.
Also, the modified Sombor index of was proposed in [6] as
(1.1) |
In addition, two other Sombor indices have been introduced: the first Banhatti-Sombor index [7]
(1.2) |
and the -Sombor index [8]
(1.3) |
here . In fact, there is a general index that includes most Sombor indices listed above: the first – index of which was introduced in [9] as
(1.4) |
with . Note that , , , and . Also, we note that equals the general sum-connectivity index [10] Reduced versions of , and were also introduced in [4,6,11], e.g., the reduced – index is
If , then is just defined for graphs without pendant vertices (recall that a vertex is said pendant if its degree is equal to ).
Since I. Gutman initiated the study of the mathematical properties of Sombor index in [4], many papers have continued this study, see e.g., [12,13,14,15,16,17,18].
Our main aim is to obtain new bounds of Sombor indices, and to characterize the graphs where equality occurs. In particular, we have obtained bounds for Sombor indices relating them with the first Zagreb index, the forgotten index and the first variable Zagreb index. Also, we solve some extremal problems for Sombor indices.
The following inequalities are known for :
and the second, third or fifth equality is attained for each if and only if . These inequalities allow to obtain the following result relating indices.
Theorem 1. Let be any graph and .Then
and the second, third, fifth or sixth equality is attained for each if and only if all the connected components of are regular graphs.
Proof. If , and , then the previous inequalities give
and the second, third or fifth equality is attained if and only if .
Hence, we obtain
and the equality in the non-strict inequalities is tight if and only if .
If we sum on these inequalities, then we obtain .
Remark 2. Note that the excluded case in Theorem 1 is not interesting, since if .
The argument in the proof of Theorem 1 also allows to obtain the following result relating reduced indices.
Theorem 3. Let be any graph and .If or , we also assume that does not have pendant vertices.Then
and the second, third, fifth or sixth equality is attained for each if and only if all the connected components of G are regular graphs.
If we take and in Theorem 1, we obtain the following inequalities for the -Sombor index.
Corollary 4. Let be any graph and .Then
and the second, third or fifth equality is attained for each if and only if all the connected components of G are regular graphs.
Recall that one of the most studied topological indices is the first Zagreb index, defined by
If we take in Corollary 4, we obtain the following result.
Corollary 5. Let be any graph and .Then
and the second, third or fifth equality is attained for each if and only if all the connected components of G are regular graphs.
If we take , and in Theorem 1, we obtain the following inequality relating the modified Sombor and the first Banhatti-Sombor indices.
Corollary 6. Let be any graph.Then
and the bound is tight if and only if all the connected components of G are regular graphs
In [19,20,21], the first variable Zagreb index is defined by
with .
Note that generalizes numerous degree–based topological indices which earlier have independently been studied. For , , , and , is, respectively, the ordinary first Zagreb index , the forgotten index , the zeroth–order Randić index , and the inverse index [2,22].
The next result relates the and indices.
Theorem 7. Let be any graph with maximum degree , minimum degree and edges, and , .Then
and the second equality is attained for some if and only if is a regular graph.
Proof. If and , then
If , then the converse inequalities hold. Hence,
Since
If , then and
Consequently, we obtain
If , then and Hölder inequality gives
Consequently, we obtain
If is regular, then
If the second equality is attained for some then we have or for each . Also, the equality in Hölder inequality gives that there exists a constant such that for every . Hence, we have either for each edge or for each edge , and hence, is regular.
If we take and in Theorem 7 we obtain:
Corollary 8. Let be any graph with maximum degree and minimum degree , and edges.Then
and the bound is tight if and only if is regular.
In order to prove Theorem 10 below we need an additional technical result. A converse of Hölder inequality appears in [23,Theorem 3], which, in the discrete case, can be stated as follows [23,Corollay 2].
Proposition 9. Consider constants and with .If satisfy for , then
where
If , then the bound is tight if and only if for each and .
Recall that a bipartite graph with and partitions is called -biregular if all vertices of have degree and all vertices of have degree .
The next result relates several indices.
Theorem 10. Let be any graph, and .Then
where
and is the constant in Proposition 9. The equality in the upper(lower) bound is tight for each if is a biregular graph (with if and only if is a regular graph.)
Proof. Hölder inequality gives
If is a biregular graph with edges, we obtain
Since
if , then
and if , then
Proposition 9 gives
Proposition 9 gives that the equality is tight in this last bound for some with if and only if
i.e., is regular.
If we take in Theorem 10 we obtain the following result.
Corollary 11. Let be any graph with edges, and .Then
The equality in the bound is tight for each if is a biregular graph.
If we take , , and in Theorem 10 we obtain the following result.
Corollary 12. Let be any graph with maximum degree , minimum degree and edges, then
The equality in the upper bound is tight if and only if is regular.The equality in the lower bound is tight if is a biregular graph.
Note that the following result improves the upper bound in Corollary 5 when .
Theorem 13. Let be any graph with minimum degree , and .Then
and the equality holds for some in each bound if and only if is regular.
Proof. The lower bound follows from Corollary 5. Let us prove the upper bound.
First of all, we are going to prove that
(2.1) |
for every and . Since (2.1) is direct for , it suffices to consider the case .
We want to compute the minimum value of the function
with the restrictions , . If is a critical point, then there exists such that
and so, and ; this fact and the equality imply
If , then and .
If , then and
Hence, and the bound is tight if and only if or . By homogeneity, we have for every and the bound is tight if and only if or . This finishes the proof of (2.1).
Consequently,
for each and . Thus,
for each and , and the equality holds for some if and only if . Therefore,
and the equality holds for some if and only if for every , i.e., is regular.
Corollary 14. Let be any graph with minimum degree .Then
and the equality holds in each bound if and only if is regular.
The upper bound in Corollary 14 appears in [14,Theorem 7]. Hence, Theorem 13 generalizes [14,Theorem 7].
A family of topological indices, named Adriatic indices, was put forward in [24,25]. Twenty of them were selected as significant predictors in Mathematical Chemistry. One of them, the inverse sum indeg index, , was singled out in [25] as a significant predictor of total surface area of octane isomers. This index is defined as
In the last years there has been an increasing interest in the mathematical properties of this index. We finish this section with two inequalities relating the Sombor, the first Zagreb and the inverse sum indeg indices.
Theorem 15. Let be any graph, then
and the upper bound is tight if and only if all the connected components of G are regular graphs.
Proof. It is well-known that for we have
and the equality
give
In a similar way, we obtain
The equality in this last inequality is tight if and only if for each edge , i.e., for every , and this happens if and only if all the connected components of G are regular graphs.
We start this section with a technical result.
Proposition 16. Let be any graph, with , and with .Then .If , then .Furthermore, if and does not have pendant vertices, then .
Proof. Let and be the sets of neighbors of and in , respectively. Since , the function
is strictly increasing in each variable if . Hence,
The same argument gives the results for the index.
Given an integer number , let (respectively, ) be the set of graphs (respectively, connected graphs) with vertices.
We study in this section the extremal graphs for the index on and .
Theorem 17. Consider with , and an integer .
The complete graph is the unique graph that maximizes on or .
Any graph that minimizes on is a path.
If is even, then the union of paths is the unique graph that minimizes on .If is odd, then the union of paths with a path isthe unique graph that minimizes on .
Furthermore, if , then the three previous statements hold if we replace with .
Proof. Let be a graph with order , minimum degree and edges.
Items and follow directly from Proposition 16.
Assume that is even. It is well known that the sum of the degrees of a graph is equal to twice the number of edges of the graph (handshaking lemma). Thus, . Since , the function
is strictly increasing in each variable if . Hence, for any graph , we have
and the equality is tight in the inequality if and only if for all , i.e., is the union of path graphs .
Finally, assume that is odd. Fix a graph . If for every , then handshaking lemma gives , a contradiction (recall that is odd). Therefore, there exists a vertex with . By handshaking lemma we have . Recall that the set of neighbors of the vertex is denoted by . Since is a strictly increasing function in each variable, we obtain
and the bound is tight if and only if for all , and . Hence, is the union of path graphs and a path graph .
If , then the same argument gives the results for the index.
We deal now with the optimization problem for when .
Given an integer number , we denote by (respectively, ) the set of graphs (respectively, connected graphs) with vertices and without pendant vertices.
Theorem 18. Consider , and an integer .
The cycle graph is the unique graph that minimizes on .
The union of cycle graphs are the only graphs that minimize on .
The complete graph is the unique graph that maximizes on or .
Proof. Let be a graph with order , minimum degree and edges. Since a graph without pendant vertices satisfies , handshaking lemma gives . Since , the function
is strictly increasing in each variable if . Hence, for any graph , we have
and the inequality is tight if and only if for all , i.e., the graph is the union of cycle graphs. If is connected, then it is the cycle graph .
Item follows from Proposition 16.
In this paper, we contributed to the study of inequalities and optimization problems associated with topological indices. In particular, we obtained new lower and upper optimal bounds of general Sombor indices, and we characterized the graphs where equality occurs.
Specifically, we have obtained inequalities for these indices relating them with other indices: the first Zagreb index, the forgotten index and the first variable Zagreb index. Finally, we solve some extremal problems for general Sombor indices
We would like to thank the reviewers by their careful reading of the manuscript and their suggestions which have improved the presentation of this work. The research of José M. Rodríguez and José M. Sigarreta was supported by a grant from Agencia Estatal de Investigación (PID2019-106433GB- ´ I00/AEI/10.13039/501100011033), Spain. The research of Jose M. Rodríguez is supported by the Madrid Government (Comunidad de Madrid-Spain) under the Multiannual Agreement with UC3M in the line of Excellence of University Professors (EPUC3M23), and in the context of the V PRICIT (Regional Programme of Research and Technological Innovation).
All authors declare no conflicts of interest in this paper.
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