Recent advances in the application of deep learning methods to forestry

Y Wang, W Zhang, R Gao, Z Jin, X Wang - Wood science and technology, 2021 - Springer
This paper provides an overview and analysis of the basic theory of deep learning (DL), and
specifically, a number of important algorithms were compared and analyzed. The article …

[HTML][HTML] Data preparation for artificial intelligence in medical imaging: A comprehensive guide to open-access platforms and tools

O Diaz, K Kushibar, R Osuala, A Linardos, L Garrucho… - Physica medica, 2021 - Elsevier
The vast amount of data produced by today's medical imaging systems has led medical
professionals to turn to novel technologies in order to efficiently handle their data and exploit …

An overview of open source deep learning-based libraries for neuroscience

LF Tshimanga, F Del Pup, M Corbetta, M Atzori - Applied Sciences, 2023 - mdpi.com
In recent years, deep learning has revolutionized machine learning and its applications,
producing results comparable to human experts in several domains, including …

Using auto-segmentation to reduce contouring and dose inconsistency in clinical trials: the simulated impact on RTOG 0617

M Thor, A Apte, R Haq, A Iyer, E LoCastro… - International Journal of …, 2021 - Elsevier
Purpose Contouring inconsistencies are known but understudied in clinical radiation
therapy trials. We applied auto-contouring to the Radiation Therapy Oncology Group …

[HTML][HTML] Cardio-pulmonary substructure segmentation of radiotherapy computed tomography images using convolutional neural networks for clinical outcomes …

R Haq, A Hotca, A Apte, A Rimner, JO Deasy… - Physics and imaging in …, 2020 - Elsevier
Background and purpose Radiation dose to the cardio-pulmonary system is critical for
radiotherapy-induced mortality in non-small cell lung cancer. Our goal was to automatically …

Cardiac radiation dose is associated with inferior survival but not cardiac events in patients with locally advanced non-small cell lung cancer in the era of immune …

N Yegya-Raman, SH Lee, C Friedes, X Wang… - Radiotherapy and …, 2024 - Elsevier
Purpose We assessed the association of cardiac radiation dose with cardiac events and
survival post-chemoradiation therapy (CRT) in patients with locally advanced non-small cell …

Prospectively-validated deep learning model for segmenting swallowing and chewing structures in CT

A Iyer, M Thor, I Onochie, J Hesse… - Physics in Medicine …, 2022 - iopscience.iop.org
Objective. Delineating swallowing and chewing structures aids in radiotherapy (RT)
treatment planning to limit dysphagia, trismus, and speech dysfunction. We aim to develop …

[HTML][HTML] Deep learning auto-segmentation and automated treatment planning for trismus risk reduction in head and neck cancer radiotherapy

M Thor, A Iyer, J Jiang, A Apte… - Physics and Imaging in …, 2021 - Elsevier
Abstract Background and Purpose Reducing trismus in radiotherapy for head and neck
cancer (HNC) is important. Automated deep learning (DL) segmentation and automated …

Interpretable machine Learning for choosing radiation dose-volume constraints on Cardio-pulmonary substructures associated with overall survival in NRG oncology …

SH Lee, H Geng, J Arnold, R Caruana, Y Fan… - International Journal of …, 2023 - Elsevier
Purpose Our objective was to use interpretable machine learning for choosing dose-volume
constraints on cardiopulmonary substructures (CPSs) associated with overall survival (OS) …

[HTML][HTML] Death without progression as an endpoint to describe cardiac radiation effects in locally advanced non-small cell lung cancer

N Yegya-Raman, TP Kegelman, SH Lee… - Clinical and …, 2023 - Elsevier
Background and purpose Prior studies have examined associations of cardiovascular
substructure dose with overall survival (OS) or cardiac events after chemoradiotherapy …