Cascaded multi-scale convolutional encoder-decoders for breast mass segmentation in high-resolution mammograms.

This paper addresses breast mass segmentation from high-resolution mammograms. To cope with strong class imbalance, huge diversity of size, shape, texture and contour as well as limited receptive field, mass segmentation is achieved through a multi-scale cascade of deep convolutional encoder-decoders without any pre-detection scheme. Multi-scale information is integrated using auto-context to make long-range spatial context arising from lower scale impact training at higher resolution. The pipeline is trained end-to-end to benefit from simultaneous segmentation refinement performed at each level. It incorporates transfer learning and fine tuning from DDSM-CBIS to INbreast datasets to further improve mass delineations. The comprehensive evaluation provided for high-resolution INbreast images highlights promising model generalizability against standard encoder-decoder strategies.

Non-invasive short-term assessment of retinoids effects on human skin in vivo using multiphoton microscopy.

BACKGROUND: The occlusive patch test developed for assessing topical retinoids activity in human skin has been extended as a short-term screening protocol for anti-ageing agents. In this model, biopsies are performed at the end of the occlusion period for morphological and immuno-histochemistry analysis. Multiphoton microscopy is a recent non-invasive imaging technique that combined with image processing tools allows the in vivo quantification of human skin modifications. OBJECTIVE: To validate with gold standards of anti-ageing that are retinoids, the relevance of multiphoton microscopy for kinetic and quantitative assessment in this model. METHODS: Twenty women, aged 50-65 years, were enrolled. Retinol 0.3% (RO) and Retinoic acid 0.025% (RA) were applied to the dorsal photo-damaged side of their forearm under occlusive patches for 12 days. A patch alone was applied to a third area as control. Evaluation was performed at day D0, D12 (end of treatment), D18 and D32 using multiphoton microscopy. Epidermal thickness, normalized area of the dermal-epidermal junction (DEJ) and melanin density were estimated using 3D image processing tools. RESULTS: Main significant results are: Epidermal thickening at D12, D18 and D32 with RO and at D12, D18 with RA vs. baseline and vs. CONTROL: Increased DEJ undulation at D32 with RO and at D12 with RA vs. baseline and vs. CONTROL: Decreased melanin content with RO (at D12 and D18 vs. baseline and at D32 vs. baseline and vs. control) and with RA (at D12 vs. baseline). CONCLUSIONS: This study shows that multiphoton microscopy associated to specific 3D image processing tools allows cutaneous effects induced by topical retinoids in this in vivo model to be non-invasively detected, quantified and followed over time. This innovative approach could be applied to the evaluation of other active compounds.

Imaging and 3D morphological analysis of collagen fibrils.

The recent booming of multiphoton imaging of collagen fibrils by means of second harmonic generation microscopy generates the need for the development and automation of quantitative methods for image analysis. Standard approaches sequentially analyse two-dimensional (2D) slices to gain knowledge on the spatial arrangement and dimension of the fibrils, whereas the reconstructed three-dimensional (3D) image yields better information about these characteristics. In this work, a 3D analysis method is proposed for second harmonic generation images of collagen fibrils, based on a recently developed 3D fibre quantification method. This analysis uses operators from mathematical morphology. The fibril structure is scanned with a directional distance transform. Inertia moments of the directional distances yield the main fibre orientation, corresponding to the main inertia axis. The collaboration of directional distances and fibre orientation delivers a geometrical estimate of the fibre radius. The results include local maps as well as global distribution of orientation and radius of the fibrils over the 3D image. They also bring a segmentation of the image into foreground and background, as well as a classification of the foreground pixels into the preferred orientations. This accurate determination of the spatial arrangement of the fibrils within a 3D data set will be most relevant in biomedical applications. It brings the possibility to monitor remodelling of collagen tissues upon a variety of injuries and to guide tissues engineering because biomimetic 3D organizations and density are requested for better integration of implants.