Deep learning identifies morphological patterns of homologous recombination deficiency in luminal breast cancers from whole slide images.

Homologous recombination DNA-repair deficiency (HRD) is becoming a well-recognized marker of platinum salt and polyADP-ribose polymerase inhibitor chemotherapies in ovarian and breast cancers. While large-scale screening for HRD using genomic markers is logistically and economically challenging, stained tissue slides are routinely acquired in clinical practice. With the objectives of providing a robust deep-learning method for HRD prediction from tissue slides and identifying related morphological phenotypes, we first show that digital pathology workflows are sensitive to potential biases in the training set, then we propose a method to overcome the influence of these biases, and we develop an interpretation method capable of identifying complex phenotypes.

In vivo multiphoton multiparametric 3D quantification of human skin aging on forearm and face.

Quantifying skin aging changes and characterizing its 3D structure and function in a non-invasive way is still a challenging area of research, constantly evolving with the development of imaging methods and image analysis tools. In vivo multiphoton imaging offers means to assess skin constituents in 3D, however prior skin aging studies mostly focused on 2D analyses of dermal fibers through their signals' intensities or densities. In this work, we designed and implemented multiphoton multiparametric 3D quantification tools for in vivo human skin pigmentation and aging characterization.

In vivo melanin 3D quantification and z-epidermal distribution by multiphoton FLIM, phasor and Pseudo-FLIM analyses.

Characterizing melanins in situ and determining their 3D z-epidermal distribution is paramount for understanding physiological/pathological processes of melanin neosynthesis, transfer, degradation or modulation with external UV exposure or cosmetic/pharmaceutical products. Multiphoton fluorescence intensity- and lifetime-based approaches have been shown to afford melanin detection, but how can one quantify melanin in vivo in 3D from multiphoton fluorescence lifetime (FLIM) data, especially since FLIM imaging requires long image acquisition times not compatible with 3D imaging in a clinical setup? We propose an approach combining (i) multiphoton FLIM, (ii) fast image acquisition times, and (iii) a melanin detection method called Pseudo-FLIM, based on slope analysis of autofluorescence intensity decays from temporally binned data. We compare Pseudo-FLIM to FLIM bi-exponential and phasor analyses of synthetic melanin, melanocytes/keratinocytes coculture and in vivo human skin.

In vivo multiphoton imaging for non-invasive time course assessment of retinoids effects on human skin.

Background: In vivo multiphoton imaging and automatic 3D image processing tools provide quantitative information on human skin constituents. These multiphoton-based tools allowed evidencing retinoids epidermal effects in the occlusive patch test protocol developed for antiaging products screening. This study aimed at investigating their relevance for non-invasive, time course assessment of retinoids cutaneous effects under real-life conditions for one year.

Waterpixels.

Many approaches for image segmentation rely on a first low-level segmentation step, where an image is partitioned into homogeneous regions with enforced regularity and adherence to object boundaries. Methods to generate these superpixels have gained substantial interest in the last few years, but only a few have made it into applications in practice, in particular because the requirements on the processing time are essential but are not met by most of them. Here, we propose waterpixels as a general strategy for generating superpixels which relies on the marker controlled watershed transformation.

Determination of collagen fiber orientation in histological slides using Mueller microscopy and validation by second harmonic generation imaging.

We studied the azimuthal orientations of collagen fibers in histological slides of uterine cervical tissue by two different microscopy techniques, namely Mueller polarimetry (MP) and Second Harmonic Generation (SHG). SHG provides direct visualization of the fibers with high specificity, which orientations is then obtained by suitable image processing. MP provides images of retardation (among other polarimetric parameters) due to the optical anisotropy of the fibers, which is enhanced by Picrosirius Red staining.

Fibrillogenesis from nanosurfaces: multiphoton imaging and stereological analysis of collagen 3D self-assembly dynamics.

The assembly of proteins into fibrillar structures is an important process that concerns different biological contexts, including molecular medicine and functional biomaterials. Engineering of hybrid biomaterials can advantageously provide synergetic interactions of the biopolymers with an inorganic component to ensure specific supramolecular organization and dynamics. To this aim, we designed hybrid systems associating collagen and surface-functionalized silica particles and we built a new strategy to investigate fibrillogenesis processes in such multicomponents systems, working at the crossroads of chemistry, physics and mathematics.

Exudate detection in color retinal images for mass screening of diabetic retinopathy.

The automatic detection of exudates in color eye fundus images is an important task in applications such as diabetic retinopathy screening. The presented work has been undertaken in the framework of the TeleOphta project, whose main objective is to automatically detect normal exams in a tele-ophthalmology network, thus reducing the burden on the readers. A new clinical database, e-ophtha EX, containing precisely manually contoured exudates, is introduced.

Parsimonious path openings and closings.

Path openings and closings are morphological tools used to preserve long, thin, and tortuous structures in gray level images. They explore all paths from a defined class, and filter them with a length criterion. However, most paths are redundant, making the process generally slow.

Multimedia data mining for automatic diabetic retinopathy screening.

This paper presents TeleOphta, an automatic system for screening diabetic retinopathy in teleophthalmology networks. Its goal is to reduce the burden on ophthalmologists by automatically detecting non referable examination records, i.e.

Automatic 3D segmentation of multiphoton images: a key step for the quantification of human skin.

Background/purpose: Multiphoton microscopy has emerged in the past decade as a useful noninvasive imaging technique for in vivo human skin characterization. However, it has not been used until now in evaluation clinical trials, mainly because of the lack of specific image processing tools that would allow the investigator to extract pertinent quantitative three-dimensional (3D) information from the different skin components.

Methods: We propose a 3D automatic segmentation method of multiphoton images which is a key step for epidermis and dermis quantification.

A multiple-instance learning framework for diabetic retinopathy screening.

A novel multiple-instance learning framework, for automated image classification, is presented in this paper. Given reference images marked by clinicians as relevant or irrelevant, the image classifier is trained to detect patterns, of arbitrary size, that only appear in relevant images. After training, similar patterns are sought in new images in order to classify them as either relevant or irrelevant images.