This is the first version of a PyTorch model trained on detecting lung organoids from 2D microscopy images. The model has been pre-trained on the OrgaQuant dataset and fine-tuned with an in-house dataset of lung organoids
In this master thesis we have adapted and implemented Mask R-CNN to the task of detecting and locali...
Lungs are crucial parts of the human body and can be captured as Chest x-ray images for disease diag...
The dataset consists of images of C. elegans in Petri Dish that were captured at a frequency of 1 Hz...
This is a PyTorch Faster RCNN model trained on detecting lung organoids from 2D microscopy images. T...
Please visit the GitHub repository below to use this pre-trained model to generate predictions for r...
Early pulmonary nodule detection is very important in lung cancer diagnosis and screening. Most stat...
a) The Faster-RCNN method detects objects directly on images without using an intermediate semantic ...
We built two types of models: a CNN to classify the Ashcroft score (used as an example in the figure...
This project is about the detection of lung cancer by training a model of deep neural networks using...
Every organism is known to have different structural and biological system, specifically in human im...
Three-dimensional (3D) spheroid models are increasingly being used in scientific research due to the...
As the basic units of the human body structure and function, cells have a considerable influence on ...
Pretrained network on the LIDC-IDRI lung nodules dataset. The network can be used as a feature extra...
Machine learning requires a human description of the data. The manual dataset description is very ti...
Organoids have immense potential as ex vivo disease models for drug discovery and personalized drug ...
In this master thesis we have adapted and implemented Mask R-CNN to the task of detecting and locali...
Lungs are crucial parts of the human body and can be captured as Chest x-ray images for disease diag...
The dataset consists of images of C. elegans in Petri Dish that were captured at a frequency of 1 Hz...
This is a PyTorch Faster RCNN model trained on detecting lung organoids from 2D microscopy images. T...
Please visit the GitHub repository below to use this pre-trained model to generate predictions for r...
Early pulmonary nodule detection is very important in lung cancer diagnosis and screening. Most stat...
a) The Faster-RCNN method detects objects directly on images without using an intermediate semantic ...
We built two types of models: a CNN to classify the Ashcroft score (used as an example in the figure...
This project is about the detection of lung cancer by training a model of deep neural networks using...
Every organism is known to have different structural and biological system, specifically in human im...
Three-dimensional (3D) spheroid models are increasingly being used in scientific research due to the...
As the basic units of the human body structure and function, cells have a considerable influence on ...
Pretrained network on the LIDC-IDRI lung nodules dataset. The network can be used as a feature extra...
Machine learning requires a human description of the data. The manual dataset description is very ti...
Organoids have immense potential as ex vivo disease models for drug discovery and personalized drug ...
In this master thesis we have adapted and implemented Mask R-CNN to the task of detecting and locali...
Lungs are crucial parts of the human body and can be captured as Chest x-ray images for disease diag...
The dataset consists of images of C. elegans in Petri Dish that were captured at a frequency of 1 Hz...
DOI
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