Python script that extract images from LUNA16 dataset to a human readable format
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Updated
Dec 26, 2022 - Python
Python script that extract images from LUNA16 dataset to a human readable format
Implementation of lung nodule detection and false positive reduction using CT images for LUNA16-LUng-Nodule-Analysis-2016-Challenge.
Full Processing on Luna16 Challange (All data resampled to 1mm x 0.7mm x 0.7mm)
Lung cancer detection using deep learning models
This study presents the development and validation of AI models for both nodule detection and cancer classification tasks. This benchmarking across multiple datasets establishes the DLCSD as a reliable resource for lung cancer AI research.
Lung Nodules Segmentation from CT scans using CNN.
Boost lung Cancer Detection using Generative model and Semi-Supervised Learning
Lung nodule detection- LUNA 16
3D-UCaps: 3D Capsules Unet for Volumetric Image Segmentation (MICCAI 2021)
Developing a well-documented repository for the Lung Nodule Detection task on the Luna16 dataset. This work is inspired by the ideas of the first-placed team at DSB2017, "grt123".
A Clone version from Original SegCaps source code with enhancements on MS COCO dataset.
LUNA16-Lung-Nodule-Analysis-2016-Challenge
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