## 6 Conclusions and Future Works  
This work addresses the cardiac segmentation in short-axis MRI by developing a multi-stage method. In the first stage, irrelevant information is removed from the input slices by extracting ROIs. The second stage performs the MYO and LVC segmentation, and the third focuses on generating RV masks.  
This segmentation process is important for the early detection and treatment of CDVs.The proposed method achieved promising results. The outcomes presented by the EAIS-Net and IRAX-Net surpass the U-Net and other networks tested. Quantitatively comparable results were obtained in the validation process on the online platform of the ACDC challenge and with the test set of the M&Ms dataset. It is important to note that our approach was developed with more limited hardware resources than most works competing on the mentioned challenges.  
Future work should explore other preprocessing techniques to deal with heterogeneous aspects of cardiac MRI image acquisition. Approaches based on Attention mechanisms [63], which can be incorporated into the composition of AIS blocks, will also be tested. Additionally, experiments with vision transformers [64] and vision mamba [65] will be conducted in each segmentation stage of the proposed method to enhance the overall results, focusing on improving the RV segmentation performance.  
Conceptualization, I.F.S.d.S., A.M.C., A.C.S., A.C.d.P. and M.G.; methodology, I.F.S.d.S.; writing--original draft, I.F.S.d.S.; investigation, I.F.S.d.S.; supervision, A.C.S., A.M.C. and A.C.d.P.; validation, A.C.S., A.M.C. and A.C.d.P.; funding acquisition, M.G. and A.M.C. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Brazilian fomenting agencies Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES)--Finance Code 001, Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq), Fundacao de Amparo a Pesquisa Desenvolvimento Cientifico e Tecnologico do Maranhao (FAPEMA), Empresa Brasileira de Servicos Hospitalares (Ebserh) Grant number 409593/2021-4, and Fundacao para a Ciencia e Tecnologia, IP (FCT) within the RD Units Project Scope: UIDB/00319/2020 (ALGORITMI).  
The data that support the findings of this study are openly available at [[https://www.creatis.insa-lyon.fr/Challenge/acdc/databases.html](https://www.creatis.insa-lyon.fr/Challenge/acdc/databases.html)]([https://www.creatis.insa-lyon.fr/Challenge/acdc/databases.html](https://www.creatis.insa-lyon.fr/Challenge/acdc/databases.html)) accessed on 19 August 2024 (ACDC Dataset) and [[https://www.ub.edu/mnmns/](https://www.ub.edu/mnmns/)]([https://www.ub.edu/mnmns/](https://www.ub.edu/mnmns/)) accessed on 19 August 2024 (M&Ms Dataset). Scripts are available at [[https://github.com/francyles/sec-method](https://github.com/francyles/sec-method)]([https://github.com/francyles/sec-method](https://github.com/francyles/sec-method)) accessed on 19 August 2024.  
The authors acknowledge the Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES), Brazil--Finance Code 001, Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq), Brazil, and Fundacao de Amparo a Pesquisa Desenvolvimento Cientifico e Tecnologico do Maranhao (FAPEMA), Brazil, Empresa Brasileira de Servicos Hospitalares(Ebserh) Grant number 409593/2021-4 and Fundacao para a Ciencia e Tecnologia, IP (FCT) within the RD Units Project Scope: UIDB/00319/2020 (ALGORITMI) for the financial support.  
The authors declare no conflicts of interest.