In subcellular biological research, fluorescence staining is a key technique to reveal the locations and morphology of subcellular structures. However, fluorescence staining is slow, expensive, and harmful to cells. In this paper, we treat it as a deep learning task termed subcellular structure prediction (SSP), aiming to predict the 3D fluorescent images of multiple subcellular structures from a 3D transmitted-light image. Unfortunately, due to the limitations of current biotechnology, each image is partially labeled in SSP. Besides, naturally, the subcellular structures vary considerably in size, which causes the multi-scale issue in SSP. However, traditional solutions can not address SSP well since they organize network parameters inefficiently and inflexibly. To overcome these challenges, we propose Re-parameterizing Mixture-of-Diverse-Experts (RepMode), a network that dynamically organizes its parameters with task-aware priors to handle specified single-label prediction tasks of SSP. In RepMode, the Mixture-of-Diverse-Experts (MoDE) block is designed to learn the generalized parameters for all tasks, and gating re-parameterization (GatRep) is performed to generate the specialized parameters for each task, by which RepMode can maintain a compact practical topology exactly like a plain network, and meanwhile achieves a powerful theoretical topology. Comprehensive experiments show that RepMode outperforms existing methods on ten of twelve prediction tasks of SSP and achieves state-of-the-art overall performance.
翻译:在亚细胞生物学研究中,荧光污点是揭示亚细胞结构的位置和形态的关键技术。 但是, 荧光污点缓慢、 昂贵且对细胞有害。 在本文中, 我们把它视为一项深层次的学习任务, 称为子细胞结构预测( SSP ), 目的是从 3D 传输光照图像中预测多细胞结构的三维荧光图像。 不幸的是, 由于当前生物技术的局限性, 每个图像都部分标在 SSP 中。 此外, 亚细胞结构在大小上差异很大, 导致 SSP 多尺度问题。 但是, 传统解决方案无法很好地解决 SSP, 因为它们组织网络参数效率低且不灵活。 为了克服这些挑战, 我们提议重新校准三维光光图像的三维光谱结构( Repmode), 一个网络动态地组织其参数, 处理SSP 具体指定的单标签预测任务。 在 Repmodedeadal- Developalal- Developal 参数中, 将Smode- deal-deal- descrialalalalalalalalal- develristration exfal lastration ex ex laft slaft slaft slaft slaft slaft s ex laft slaft slaft laft slaft slaft laft s laft laft s laft s s s s str ex lauts laft laft sal laft sal laft laft sal laft laft laft, laft sal res laft laft laft laft laft laft laft sal 。 Sal 。, 。 Slaft 。 Sal 。 。 。 Sal 。 Sal 。 Slaction sal 。 Sal 。 工作 工作 工作, 工作 工作 工作 工作 工作 工作 工作 工作, 工作是用来为Smal,, 。 。 。 Smodalalalal 。 。 Smostral- sal- sal 。 Sal- sal- sal-