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Found 8 papers, 3 papers with code
Framing image registration as a landmark detection problem for better representation of clinical relevance
Nowadays, registration methods are typically evaluated based on sub-resolution tracking error differences.
Generative Adversarial Networks based Skin Lesion Segmentation
Skin cancer is a serious condition that requires accurate diagnosis and treatment.
Primitive Simultaneous Optimization of Similarity Metrics for Image Registration
Even though simultaneous optimization of similarity metrics is a standard procedure in the field of semantic segmentation, surprisingly, this is much less established for image registration.
Detecting Histologic & Clinical Glioblastoma Patterns of Prognostic Relevance
Glioblastoma is the most common and aggressive malignant adult tumor of the central nervous system, with a grim prognosis and heterogeneous morphologic and molecular profiles.
Deep Learning based Novel Cascaded Approach for Skin Lesion Analysis
We explored the effectiveness of deep convolutional neural network based architectures by designing an encoder-decoder architecture for skin lesion segmentation and CNN based classification network.
The Brain Tumor Sequence Registration (BraTS-Reg) Challenge: Establishing Correspondence Between Pre-Operative and Follow-up MRI Scans of Diffuse Glioma Patients
Registration of longitudinal brain MRI scans containing pathologies is challenging due to dramatic changes in tissue appearance.
GaNDLF: A Generally Nuanced Deep Learning Framework for Scalable End-to-End Clinical Workflows in Medical Imaging
Deep Learning (DL) has the potential to optimize machine learning in both the scientific and clinical communities.
The 1st Agriculture-Vision Challenge: Methods and Results
The first Agriculture-Vision Challenge aims to encourage research in developing novel and effective algorithms for agricultural pattern recognition from aerial images, especially for the semantic segmentation task associated with our challenge dataset.
