Xiaohui Xie

TL;DR: This paper's proposed end-to-end convolutional neural network model, called AttentionAnatomy, can be jointly trained with three partially annotated datasets, segmenting OARs from whole body, and presented significant improvements in both Sørensen-Dice coefficient (DSC) and 95% Hausdorff distance compared to the baseline model.

TL;DR: This work provides insights into improving the interpretability of pre-trained models and the guidance of incorporating IR axioms or human heuristics into pre-training methods.

TL;DR: A thorough comparison of variants of preference judgments for web image search finds that compared to strict preference judgments, weak preference judgments require less time and have better inter-assessor agreement.

TL;DR: SAILER as mentioned in this paper adopts the conventional encoder-decoder framework to learn the latent representation but imposes additional constraints to ensure the independence of the learned representations from the confounding factors.

TL;DR: CHYRON represents a conceptual advance in DNA recording technologies where writing rather than erasing becomes the primary mode of information accumulation, and should lead to single-cell-resolution recording of lineage and other information through long periods of time in complex animals or tumors, advancing the pursuit of a full picture of mammalian development.