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Sökning: WFRF:(Catanese L)

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  • 2017
  • swepub:Mat__t
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  • Garrucho, L, et al. (författare)
  • High-resolution synthesis of high-density breast mammograms: Application to improved fairness in deep learning based mass detection
  • 2023
  • Ingår i: Frontiers in oncology. - : Frontiers Media SA. - 2234-943X. ; 12, s. 1044496-
  • Tidskriftsartikel (refereegranskat)abstract
    • Computer-aided detection systems based on deep learning have shown good performance in breast cancer detection. However, high-density breasts show poorer detection performance since dense tissues can mask or even simulate masses. Therefore, the sensitivity of mammography for breast cancer detection can be reduced by more than 20% in dense breasts. Additionally, extremely dense cases reported an increased risk of cancer compared to low-density breasts. This study aims to improve the mass detection performance in high-density breasts using synthetic high-density full-field digital mammograms (FFDM) as data augmentation during breast mass detection model training. To this end, a total of five cycle-consistent GAN (CycleGAN) models using three FFDM datasets were trained for low-to-high-density image translation in high-resolution mammograms. The training images were split by breast density BI-RADS categories, being BI-RADS A almost entirely fatty and BI-RADS D extremely dense breasts. Our results showed that the proposed data augmentation technique improved the sensitivity and precision of mass detection in models trained with small datasets and improved the domain generalization of the models trained with large databases. In addition, the clinical realism of the synthetic images was evaluated in a reader study involving two expert radiologists and one surgical oncologist.
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  • Yin, XY, et al. (författare)
  • Genome-wide meta-analysis identifies multiple novel associations and ethnic heterogeneity of psoriasis susceptibility
  • 2015
  • Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 6, s. 6916-
  • Tidskriftsartikel (refereegranskat)abstract
    • Psoriasis is a common inflammatory skin disease with complex genetics and different degrees of prevalence across ethnic populations. Here we present the largest trans-ethnic genome-wide meta-analysis (GWMA) of psoriasis in 15,369 cases and 19,517 controls of Caucasian and Chinese ancestries. We identify four novel associations at LOC144817, COG6, RUNX1 and TP63, as well as three novel secondary associations within IFIH1 and IL12B. Fine-mapping analysis of MHC region demonstrates an important role for all three HLA class I genes and a complex and heterogeneous pattern of HLA associations between Caucasian and Chinese populations. Further, trans-ethnic comparison suggests population-specific effect or allelic heterogeneity for 11 loci. These population-specific effects contribute significantly to the ethnic diversity of psoriasis prevalence. This study not only provides novel biological insights into the involvement of immune and keratinocyte development mechanism, but also demonstrates a complex and heterogeneous genetic architecture of psoriasis susceptibility across ethnic populations.
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