Titlebook: Clinical Image-Based Procedures,Fairness of AI in Medical Imaging, and Ethical and Philosophical Iss; 12th International W Stefan Wesarg,Es

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Towards Fine-Grained Polyp Segmentation and?Classificationnd removal during the same procedure. During the last decades, several efforts have been made to develop CAD systems to assist clinicians in lesion detection and classification. Regarding the latter, and in order to be used in the exploration room as part of resect and discard or leave-in-situ strat

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Range-Of-Motion

Deep Learning-Based Fast MRI Reconstruction: Improving Generalization for?Clinical Translationruction from undersampled ‘k-space’ (Fourier domain) data. However, these methods have shown instability when faced with variations in the acquisition process and anatomical distribution. This instability indicates that DNN architectures have poorer generalization compared to their classical counter

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Uncertainty Based Border-Aware Segmentation Network for?Deep Cariesas inflammation and apical periodontitis. According to clinical evidence, carious dentin can be categorized into soft, firm, and hard dentin based on its hardness. Precise assessment of carious lesions is critical for effective treatment; however, current methods rely on subjective judgments based o

nostrum

An Efficient and?Accurate Neural Network Tool for?Finding Correlation Between Gene Expression and?Hies influencing tumor morphology are not entirely comprehended. Here, we present RNALerner, an innovative tool designed to expedite the identification of correlations between gene expression and tumor morphology as presented in H&E WSI. RNALerner achieves its efficiency by transforming the problem fr

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