mozanunal.com / PapersPapersJune 12, 2025 · 1 min readPaperVenueYearCited byAn Unsupervised Reconstruction Method for Low-Dose CT Using Deep Generative Regularization PriorBiomedical Signal Processing and Control 75, 103598202224Self-Supervised Training for Low-Dose CT Reconstruction2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), pp. 69-72202115Proj2Proj: Self-Supervised Low-Dose CT ReconstructionPeerJ Computer Science 10, e18492024133D U-NeTR: Low-Dose Computed Tomography Reconstruction via Deep Learning and 3-Dimensional ConvolutionsarXiv 2105.14130202112Prompt-Conditioned FiLM and Multi-Scale Fusion on MedSigLIP for Low-Dose CT Quality AssessmentarXiv 2511.122562025Deep Unfolded BM3D: Unrolling Non-local Collaborative Filtering into a Trainable Neural NetworkarXiv 2511.122482025Learnable Total Variation with Lambda Mapping for Low-Dose CT DenoisingarXiv 2511.105002025Task-Adaptive Low-Dose CT ReconstructionarXiv 2511.070942025LMM-IQA: Image Quality Assessment for Low-Dose CT ImagingarXiv 2511.072982025Determination of the Time of Calving in Holstein-Friesian and Simmental Cows by Using a Novel Intravaginal Temperature Recording Smart DeviceReproduction in Domestic Animals 54, 67-672019Citation counts were captured from Google Scholar and may change over time.← Projects