ABSTRACT
To enhance the viewer experience of standard dynamic range (SDR) video content on high dynamic range (HDR) displays, inverse tone mapping (ITM) is employed. Objective visual quality assessment (VQA) models are needed for effective evaluation of ITM algorithms. However, there is a lack of specialized VQA models for assessing the visual quality of inversely tone-mapped HDR videos (ITM-HDR-Videos). This paper addresses both an algorithmic and a dataset gap by introducing a novel SDR referenced HDR (SD-R-HD) VQA model tailored for ITM-HDR-Videos, along with the first public dataset specifically constructed for this purpose. The innovations of the SD-R-HD VQA model include 1) utilizing available SDR video as a reference signal, 2) extracting features that characterize standard ITM operations such as global mapping and local compensation, and 3) directly modeling interframe inconsistencies introduced by ITM operations. The newly created ITM-HDR-VQA dataset comprises 200 ITM-HDR-Videos annotated with mean opinion scores, gathered over 320 man-hours of psychovisual experiments. Experimental results demonstrate that the SD-R-HD VQA model significantly outperforms existing state-of-the-art VQA models.
ABSTRACT
BACKGROUND: Uterine Corpus Endometrial Carcinoma (UCEC) is a common malignancy of the female genital tract. The sine oculis homeobox homolog 1 (SIX1) protein has been documented to be important for tumor progression. However, little is known about the relationship between SIX1 and the pathogenesis of UCEC. OBJECTIVE: This study aimed to assess the prognostic value of biomarker SIX1 in UCEC by analyzing clinical traits, immune infiltration, and gene set enrichment analysis. METHODS: The Wilcoxon signed-rank test and logistic regression were used to analyze the relationship between clinicopathological characteristics and SIX1. The Kaplan-Meier method was used to assess the relationship between clinicopathological characteristics and prognosis verified by immunohistochemistry (IHC). Then gene set enrichment analysis (GSEA) was performed to explore signaling pathways correlated with SIX1 expression in UCEC. Finally, the TIMER2 database was used to analyze the correlation between SIX1 and immune infiltration, and the effect of SIX1 expression on immune cells was calculated with the CIBERSORT algorithm. RESULTS: We found that the expression of SIX1 in UCEC was up-regulated and correlated with a poor prognosis. Analysis showed that the expression of SIX1 was related to various clinical features and was an independent prognostic factor of UCEC. Enrichment analysis showed that SIX1 promoted the occurrence and development of UCEC by regulating multiple signaling pathways. The results of immune infiltration analysis showed that SIX1 has a complex correlation with immune infiltration. CONCLUSION: Our findings indicate that SIX1 is a promising biomarker for predicting the prognosis of UCEC and is a potential therapeutic target.
