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Found 8 papers, 3 papers with code
Deep, convergent, unrolled half-quadratic splitting for image deconvolution
Through extensive experimental studies, we verify that our approach achieves competitive performance with state-of-the-art unrolled layer-specific learning and significantly improves over the traditional HQS algorithm.
Lens-to-lens bokeh effect transformation. NTIRE 2023 challenge report
We present the new Bokeh Effect Transformation Dataset (BETD), and review the proposed solutions for this novel task at the NTIRE 2023 Bokeh Effect Transformation Challenge.
PIMIP: An Open Source Platform for Pathology Information Management and Integration
However, there is still a lack of an open and universal digital pathology platform to assist doctors in the management and analysis of digital pathological sections, as well as the management and structured description of relevant patient information.
A Personalized Diagnostic Generation Framework Based on Multi-source Heterogeneous Data
In this study, we propose a framework that combines pathological images and medical reports to generate a personalized diagnosis result for individual patient.
A Precision Diagnostic Framework of Renal Cell Carcinoma on Whole-Slide Images using Deep Learning
Tumor region detection, subtype and grade classification are the fundamental diagnostic indicators for renal cell carcinoma (RCC) in whole-slide images (WSIs).
Nuclei Grading of Clear Cell Renal Cell Carcinoma in Histopathological Image by Composite High-Resolution Network
In this paper, we propose a Composite High-Resolution Network for ccRCC nuclei grading.
OpenHI2 -- Open source histopathological image platform
Transition from conventional to digital pathology requires a new category of biomedical informatic infrastructure which could facilitate delicate pathological routine.
Effects of annotation granularity in deep learning models for histopathological images
In classification, state-of-the-art deep learning-based classifiers perform better when trained by pixel-wise annotation dataset.
