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In this paper, we extend the popular dictionary pair learning (DPL) into the scenario of twin-projective latent flexible DPL under a structured twin-incoherence. Technically, a novel framework called Twin-Projective Latent Flexible DPL (TP-DPL) is proposed, which minimizes the twin-incoherence constrained flexibly-relaxed reconstruction error to avoid the possible over-fitting issue and produce accurate reconstruction. In this setting, our TP-DPL integrates the twin-incoherence based latent flexible DPL and the joint embedding of codes as well as salient features by twin-projection into a unified model in an adaptive neighborhood-preserving manner. As a result, TP-DPL unifies the salient feature extraction, representation and classification. The twin-incoherence constraint on codes and features can explicitly ensure high intra-class compactness and inter-class separation over them. TP-DPL also integrates the adaptive weighting to preserve the local neighborhood of the coefficients and salient features within each class explicitly. For efficiency, TP-DPL uses Frobenius-norm and abandons the costly l0/l1-norm for group sparse representation. Another byproduct is that TP-DPL can directly apply the class-specific twin-projective reconstruction residual to compute the label of data. Extensive results on public databases show that TP-DPL can deliver the state-of-the-art performance. Index Terms-Structured twin-incoherence, twin-projective latent dictionary pair learning, structured adaptive weighting, discriminative classification I.

In whole slide imaging (WSI), normally only a one layer imaging of the slide is performed. Autofocus at multiple positions is usually required. But defocus blur still exists due to tissue folding or specimen thickness. Repeated Z‐stack scan be applied here, which, however, is too time consuming. Here, a high throughput slanted scanning WSI system is reported. In this system, the slide surface was slanted 1° relative to the focal plane. Thus, the focal plane spanned multiple layers of the sample. By moving the slide, multi‐layer image data of the sample can be acquired simultaneously at a time frame comparable to conventional 1‐layer imaging. With image fusion, defocus blur can be avoided. High quality and fast imaging of both cytological and histological slide specimens was demonstrated without applying aberration correction. The system can be a highly efficient way for the application of WSI in digital pathology.

10 pages, 6 figures

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