Ayano Kuwada, Ikuko Mohri, Ryosuke Asano, Shigeyuki Matsuzawa, Kumi Kato-Nishimura, Ikuko Hirata, Takashi Mitsuhosi, Kuriko Kagitani-Shimono, Mariko Nakanishi, Masaya Tachibana, Yuko Ohno, Masako Taniike
Japanese Sleep Questionnaire for Elementary Schoolers (JSQ-ES): validation and population-based score distribution
Sleep medicine
aimed improve image quality iq sparseview computed tomography ct images using unet lung metastasis detection determine best tradeoff number views iq diagnostic confidence ct images 41 subjects aged 628 106 years mean standard deviation 23 men 34 lung metastasis 7 healthy retrospectively selected 20162018 forward projected onto 2048view sinograms six corresponding sparseview ct data subsets varying levels undersampling reconstructed sinograms using filtered backprojection 16 32 64 128 256 512 views dualframe unet trained evaluated subsampling level 8658 images 22 diseased subjects representative image per scan selected 19 subjects 12 diseased 7 healthy singleblinded multireader study slices levels subsampling without unet postprocessing presented three readers iq diagnostic confidence ranked using predefined scales subjective nodule segmentation evaluated using sensitivity dice similarity coefficient dsc clustered wilcoxon signedrank test used 64projection sparseview images resulted 089 sensitivity 081 dsc counterparts postprocessed unet improved metrics 094 sensitivity 085 dsc p 0400 fewer views led insufficient iq diagnosis increased views substantial discrepancies noted sparseview postprocessed images projection views reduced 2048 64 maintaining iq confidence radiologists satisfactory level reader study demonstrates benefit unet postprocessing regular ct screenings patients lung metastasis increase iq diagnostic confidence reducing dose sparseprojectionview streak artifacts reduce quality usability sparseview ct images unetbased postprocessing removes sparseview artifacts maintaining diagnostically accurate iq postprocessed sparseview cts drastically increase radiologists confidence diagnosing lung metastasis