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Tumor segmentation on whole slide images: training or prompting? Open
Tumor segmentation stands as a pivotal task in cancer diagnosis. Given the immense dimensions of whole slide images (WSI) in histology, deep learning approaches for WSI classification mainly operate at patch-wise or superpixel-wise level. …
giRAff: an automated atlas segmentation tool adapted to single histological slices Open
Conventional histology of the brain remains the gold standard in the analysis of animal models. In most biological studies, standard protocols usually involve producing a limited number of histological slices to be analyzed. These slices a…
Mu-Net a Light Architecture for Small Dataset Segmentation of Brain Organoid Bright-Field Images Open
To characterize the growth of brain organoids (BOs), cultures that replicate some early physiological or pathological developments of the human brain are usually manually extracted. Due to their novelty, only small datasets of these images…
Brain organoid data synthesis and evaluation Open
Introduction Datasets containing only few images are common in the biomedical field. This poses a global challenge for the development of robust deep-learning analysis tools, which require a large number of images. Generative Adversarial N…
Adversarial Stain Transfer to Study the Effect of Color Variation on Cell Instance Segmentation Open
Stain color variation in histological images, caused by a variety of factors, is a challenge not only for the visual diagnosis of pathologists but also for cell segmentation algorithms. To eliminate the color variation, many stain normaliz…
Automated Atlas-based Segmentation of Single Coronal Mouse Brain Slices using Linear 2D-2D Registration Open
A significant challenge for brain histological data analysis is to precisely identify anatomical regions in order to perform accurate local quantifications and evaluate therapeutic solutions. Usually, this task is performed manually, becom…
Evaluation of Deep Learning Topcoders Method for Neuron Individualization in Histological Macaque Brain Section Open
Cell individualization has a vital role in digital pathology image analysis. Deep Learning is considered as an efficient tool for instance segmentation tasks, including cell individualization. However, the precision of the Deep Learning mo…
Evaluation of Deep Learning Topcoders Method for Neuron Individualization in Histological Macaque Brain Section Open
Cell individualization has a vital role in digital pathology image analysis. Deep Learning is considered as an efficient tool for instance segmentation tasks, including cell individualization. However, the precision of the Deep Learning mo…
Automated Atlas-based Segmentation of Single Coronal Mouse Brain Slices using Linear 2D-2D Registration Open
A significant challenge for brain histological data analysis is to precisely identify anatomical regions in order to perform accurate local quantifications and evaluate therapeutic solutions. Usually, this task is performed manually, becom…
Recent Trends and Perspectives in Cerebral Organoids Imaging and Analysis Open
Purpose: Since their first generation in 2013, the use of cerebral organoids has spread exponentially. Today, the amount of generated data is becoming challenging to analyze manually. This review aims to overview the current image acquisit…
A novel approach for high-resolution image reconstruction for in-vivo fetal brain MRI Open
In the present study, we propose an automatic framework for obtaining an accurate representation of the in-vivo fetal brain for the quantification of cerebral volume and cortical surface. One of the biggest