Hi! Welcome to my personal website!
I am Clément, I am a postdoc researcher in bioimage analysis.
Publications
Journal articles:
-
Sketchpose: learning to segment cells with partial annotations
Cazorla C., Munier N., Morin R., Weiss P.
HAL (2023) -
Svetlana a Supervised Segmentation Classifier for Napari
Cazorla C., Morin R., Weiss P.
Scientific Reports (2024) -
SegSRGAN: Super-resolution and segmentation using generative adversarial networks — Application to neonatal brain MRI
Delannoy Q., Pham C., Cazorla C., Tor-Díez C., Dollé G., Meunier H., Bednarek N., Fablet R., Passat N., Rousseau F.
Computers in Biology and Medicine, Volume 120 (2020) -
Watervoxels
Cettour-Janet P., Cazorla C. , Machairas V., Delannoy Q., Bednarek N., Rousseau F., Decencière E., Passat N.
IPOL Journal · Image Processing On Line (2019)
Conference article:
- SVETLANA: UN CLASSIFIEUR DE SEGMENTATION POUR NAPARI
Cazorla C., Morin R., Weiss P.
Colloque GRETSI, Nancy (2022)
YouTube content
YouTube tutorial of my Napari plugin called Svetlana.
About Me
I obtained my engineering degree from ENSEEIHT (Toulouse) in electronics and signal processing in 2017, then I worked as an image processing engineer in the space industry (CNES, CS), and finally as a research engineer on MRI imaging at the university of Reims.
I did my PhD thesis in Toulouse (France), supervised by Pierre Weiss (CNRS), where I shared my time between the CBI (Centre de Biologie Intégrative) of Toulouse, and Imactiv-3D company. My PhD work were mainly oriented towards the exploration of minimalist convolutional neural networks for segmentation and classification tasks using a small amount of annotations for microscopy images. With this in mind, I developed and keep maintaining two Napari plugin:
- Svetlana, which is dedicated to classifying segmentation masks by quickly annotating a small amount of ROI (see 3D result in the video below).
- Sketchpose, which is dedicated to segmenting cells and bacteria by quickly training an Omnipose-based CNN using sparse annotations.