Colin Jacobs

Orcid: 0000-0003-1180-3805

According to our database1, Colin Jacobs authored at least 42 papers between 2011 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Nodule Detection and Generation on Chest X-Rays: NODE21 Challenge.
IEEE Trans. Medical Imaging, August, 2024

Structure and position-aware graph neural network for airway labeling.
Medical Image Anal., 2024

Optimization of Approximate Maps for Linear Systems Arising in Discretized PDEs.
CoRR, 2024

Towards automatic forecasting of lung nodule diameter with tabular data and CT imaging.
Biomed. Signal Process. Control., 2024

2023
Dataset for: Kidney abnormality segmentation in thorax-abdomen CT scans.
Dataset, June, 2023

Dense regression activation maps for lesion segmentation in CT scans of COVID-19 patients.
Medical Image Anal., May, 2023

The Liver Tumor Segmentation Benchmark (LiTS).
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Medical Image Anal., 2023

Transfer learning from a sparsely annotated dataset of 3D medical images.
CoRR, 2023

Kidney abnormality segmentation in thorax-abdomen CT scans.
CoRR, 2023

Emphysema Subtyping on Thoracic Computed Tomography Scans using Deep Neural Networks.
CoRR, 2023

Reproducibility of Training Deep Learning Models for Medical Image Analysis.
Proceedings of the Medical Imaging with Deep Learning, 2023

2022
Automated COVID-19 Grading With Convolutional Neural Networks in Computed Tomography Scans: A Systematic Comparison.
IEEE Trans. Artif. Intell., 2022

Exploring the interpretability of deep neural networks used for gravitational lens finding with a sensitivity probe.
Astron. Comput., 2022

2021
Deep Clustering Activation Maps for Emphysema Subtyping.
CoRR, 2021

Dense Regression Activation Maps For Lesion Segmentation in CT scans of COVID-19 patients.
CoRR, 2021

What happened here? Children integrate physical reasoning to infer actions from indirect evidence.
Proceedings of the 43rd Annual Meeting of the Cognitive Science Society, 2021

2020
Surveying the reach and maturity of machine learning and artificial intelligence in astronomy.
WIREs Data Mining Knowl. Discov., 2020

Relational Modeling for Robust and Efficient Pulmonary Lobe Segmentation in CT Scans.
IEEE Trans. Medical Imaging, 2020

"Sensie": Probing the sensitivity of neural networks.
J. Open Source Softw., 2020

Improving Automated COVID-19 Grading with Convolutional Neural Networks in Computed Tomography Scans: An Ablation Study.
CoRR, 2020

Contextual Two-Stage U-Nets for Robust Pulmonary Lobe Segmentation in CT Scans of COVID-19 and COPD Patients.
CoRR, 2020

Feasibility of end-to-end trainable two-stage U-Net for detection of axillary lymph nodes in contrast-enhanced CT based on sparse annotations.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020

2019
LUNA16 Part 2/2.
Dataset, March, 2019

LUNA16 Part 2/2.
Dataset, March, 2019

LUNA16 Part 1/2.
Dataset, March, 2019

LUNA16 Part 1/2.
Dataset, March, 2019

LUNA16 Part 2/2.
Dataset, March, 2019

LUNA16 Part 1/2.
Dataset, March, 2019

The Liver Tumor Segmentation Benchmark (LiTS).
CoRR, 2019

2018
iW-Net: an automatic and minimalistic interactive lung nodule segmentation deep network.
CoRR, 2018

Towards an Automatic Lung Cancer Screening System in Low Dose Computed Tomography.
Proceedings of the Image Analysis for Moving Organ, Breast, and Thoracic Images, 2018

2017
Organ detection in thorax abdomen CT using multi-label convolutional neural networks.
Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017

2016
Pulmonary Nodule Detection in CT Images: False Positive Reduction Using Multi-View Convolutional Networks.
IEEE Trans. Medical Imaging, 2016

Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: the LUNA16 challenge.
CoRR, 2016

Towards automatic pulmonary nodule management in lung cancer screening with deep learning.
CoRR, 2016

2015
Bag-of-Frequencies: A Descriptor of Pulmonary Nodules in Computed Tomography Images.
IEEE Trans. Medical Imaging, 2015

Computer-aided detection of lung cancer: combining pulmonary nodule detection systems with a tumor risk prediction model.
Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015

Automatic detection of spiculation of pulmonary nodules in computed tomography images.
Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015

Off-the-shelf convolutional neural network features for pulmonary nodule detection in computed tomography scans.
Proceedings of the 12th IEEE International Symposium on Biomedical Imaging, 2015

2014
Automatic detection of subsolid pulmonary nodules in thoracic computed tomography images.
Medical Image Anal., 2014

Automated detection and quantification of micronodules in thoracic CT scans to identify subjects at risk for silicosis.
Proceedings of the Medical Imaging 2014: Computer-Aided Diagnosis, 2014

2011
Computer-Aided Detection of Ground Glass Nodules in Thoracic CT Images Using Shape, Intensity and Context Features.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011, 2011


  Loading...