The impact of deep learning aid on the workload and interpretation accuracy of radiologists on chest computed tomography: a cross-over reader study

no code implementations • 12 Jun 2024 • Anvar Kurmukov, Valeria Chernina, Regina Gareeva, Maria Dugova, Ekaterina Petrash, Olga Aleshina, Maxim Pisov, Boris Shirokikh, Valentin Samokhin, Vladislav Proskurov, Stanislav Shimovolos, Maria Basova, Mikhail Goncahrov, Eugenia Soboleva, Maria Donskova, Farukh Yaushev, Alexey Shevtsov, Alexey Zakharov, Talgat Saparov, Victor Gombolevskiy, Mikhail Belyaev

Previous studies have measured the time-saving effect of using a deep-learning-based aid (DLA) for CT interpretation.

Computed Tomography (CT) Diagnostic +1

Adaptation to CT Reconstruction Kernels by Enforcing Cross-domain Feature Maps Consistency

no code implementations • 28 Mar 2022 • Stanislav Shimovolos, Andrey Shushko, Mikhail Belyaev, Boris Shirokikh

In this paper, we show a decrease in the COVID-19 segmentation quality of the model trained on the smooth and tested on the sharp reconstruction kernels.

Computed Tomography (CT) CT Reconstruction +1