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Filtragem de ruído Poisson utilizando o algoritmo BM3D com distâncias estocásticas e transformações de estabilização de variância
(Universidade Federal de São Carlos, 2024-12-04) Abegão, Rodrigo Garcia; Levada, Alexandre Luis Magalhães; https://lattes.cnpq.br/3341441596395463; https://orcid.org/0000-0001-8253-2729; https://lattes.cnpq.br/6988113472226135
Noise in images is a phenomenon present in several fields of academic research, dueto the fact that its presence in them can impair the analysis and interpretation of datacontained in them. Thus, generating significant implications in areas such as: medicine,biological sciences, astronomy and geology, among others.In the medical field, images generated by tomographs are degraded by a noise calledPoisson. This is a statistical and signal-dependent noise caused by the absorption andscattering phenomena caused during the interaction between the X-ray beam and matter.This type of noise is caused by several sources, including variations in light intensity,measurement errors, electromagnetic interference and electronic noise.There are several filters to mitigate the presence of Poisson noise in images. And, themost used techniques in this environment are non-local, such as BM3D. The purpose ofwhich is the similarity between small equivalent fragments in the image, called patchessuch that the state of the art generally adopts the Euclidean distance in cases of AWGN.This research proposes the use of stochastic distances in the BM3D algorithm toachieve results superior to the current state of the art. The incorporation of stochasticdistances enables the exploration of innovative approaches that take into account differentcharacteristics of data distributions. This approach significantly expands the possibilitiesfor analyzing and comparing random variables, providing a more comprehensive and detailedunderstanding of the relationships and patterns present in the data. To achievethese objectives, the variance-stabilizing technique known as VST was used to transformPoisson noise into AWGN. Several studies demonstrate the effectiveness of using differentdistances, although performance depends on the specific type of noise present in the data.
Dengue na atenção primária em saúde: uso do mapa de fluxo de valor da filosofia lean healthcare
(Universidade Federal de São Carlos, 2024-12-04) Mendes, Sara de França; Feliciano, Adriana Barbieri; http://lattes.cnpq.br/9398810638733882; https://orcid.org/0000-0003-2524-9876; http://lattes.cnpq.br/2954187762144602; https://orcid.org/0009-0005-9887-5511; Gabassa, Valeria Cristina; Padilha, Roberto de Queiroz; http://lattes.cnpq.br/1340521331912418; http://lattes.cnpq.br/2262980850254605; https://orcid.org/0000-0001-8066-5501; https://orcid.org/0000-0001-8753-1151
Introduction: Primary Health Care (PHC) plays a central role in the organization of care within Brazil’s Unified Health System, particularly in the management of infectious and neglected diseases. However, PHC services still face challenges related to fragmented workflows, inefficiencies, and operational waste. In this context, Lean Healthcare emerges as a promising approach to reorganize care processes, focusing on waste reduction and value generation for users. Objective: To analyze and redesign the care flow for patients with suspected dengue in a Primary Health Care Unit in the Federal District, using Value Stream Mapping (VSM) as a Lean Healthcare tool. Method: This qualitative intervention study was conducted in a Primary Health Care setting with the participation of a multidisciplinary health team. Data collection was carried out through participatory workshops, during which the current care flow was mapped, bottlenecks and inefficiencies were identified, and a future-state care flow was collaboratively developed. The analysis was guided by Lean Healthcare principles and Clinical Governance, aligned with national dengue management guidelines. Results: The current-state VSM revealed weaknesses such as long waiting times, communication failures, task duplication, lack of standardization, incompatibility among information systems, and irregular supply of materials. The future-state VSM incorporated improvements including reorganization of triage, clearer definition of professional roles, enhanced integration among nursing, medical, and laboratory services, and strengthened coordination between surveillance and care. These changes were characterized by low implementation cost and high potential impact. Final considerations: Lean Healthcare proved to be feasible and effective in PHC, contributing to the reorganization of dengue care flows, improved service responsiveness, and strengthened clinical governance. The participatory use of VSM supported collaborative work processes and sustainable improvements, particularly in socially vulnerable territories. The findings highlight the relevance of expanding Lean Healthcare applications in non-hospital settings to strengthen PHC and health care networks.