[HTML][HTML] Prior-aware autoencoders for lung pathology segmentation

M Astaraki, Ö Smedby, C Wang - Medical Image Analysis, 2022 - Elsevier
Segmentation of lung pathology in Computed Tomography (CT) images is of great
importance for lung disease screening. However, the presence of different types of lung …

[HTML][HTML] Wavelet transformation can enhance computed tomography texture features: a multicenter radiomics study for grade assessment of COVID-19 pulmonary …

Z Jiang, J Yin, P Han, N Chen, Q Kang… - … imaging in medicine …, 2022 - ncbi.nlm.nih.gov
Background This study set out to develop a computed tomography (CT)-based wavelet
transforming radiomics approach for grading pulmonary lesions caused by COVID-19 and to …

CTumorGAN: a unified framework for automatic computed tomography tumor segmentation

S Pang, A Du, MA Orgun, Z Yu, Y Wang… - European journal of …, 2020 - Springer
Purpose Unlike the normal organ segmentation task, automatic tumor segmentation is a
more challenging task because of the existence of similar visual characteristics between …

The application of machine learning and deep learning radiomics in the treatment of esophageal cancer

J Yi, Y Wu, B Ning, J Zhang, M Pleshkov… - Radiation Medicine …, 2023 - mednexus.org
Esophageal cancer (EC) is a very aggressive disease with most cases diagnosed at
advanced stages. Early detection and prognosis prediction are of clinical significance in the …

Lung cancer tumor region segmentation using recurrent 3d-denseunet

U Kamal, AM Rafi, R Hoque, J Wu… - Thoracic Image Analysis …, 2020 - Springer
The performance of a computer-aided automated diagnosis system of lung cancer from
Computed Tomography (CT) volumetric images greatly depends on the accurate detection …

A pipeline for lung tumor detection and segmentation from CT scans using dilated convolutional neural networks

S Hossain, S Najeeb, A Shahriyar… - ICASSP 2019-2019 …, 2019 - ieeexplore.ieee.org
Lung cancer is the most prevalent cancer worldwide with about 230,000 new cases every
year. Most cases go undiagnosed until it's too late, especially in develo** countries and …

[HTML][HTML] Development and validation of novel radiomics-based nomograms for the prediction of EGFR mutations and Ki-67 proliferation index in non-small cell lung …

Y Dong, Z Jiang, C Li, S Dong, S Zhang… - … Imaging in Medicine …, 2022 - ncbi.nlm.nih.gov
Background: We developed and validated novel radiomics-based nomograms to identify
epidermal growth factor receptor (EGFR) mutations and the Ki-67 proliferation index of non …

Development and externally validate MRI-based nomogram to assess EGFR and T790M mutations in patients with metastatic lung adenocarcinoma

Y Fan, Y Dong, H Wang, H Wang, X Sun, X Wang… - European …, 2022 - Springer
Objectives This study aims to explore values of multi-parametric MRI–based radiomics for
detecting the epidermal growth factor receptor (EGFR) mutation and resistance (T790M) …

Detection of Head Raising Rate of Students in Classroom Based on Head Posture Recognition.

Q Guo - Traitement du Signal, 2020 - search.ebscohost.com
The proliferation of smart mobile terminals has weakened the attention and reduced the
learning efficiency of students, making them more likely to lower their heads. To quantify the …

Development and validation of MRI-based radiomics signatures as new markers for preoperative assessment of EGFR mutation and subtypes from bone metastases

Y Fan, Y Dong, X Sun, H Wang, P Zhao, H Wang… - BMC cancer, 2022 - Springer
Background This study aimed to develop and externally validate contrast-enhanced (CE) T1-
weighted MRI-based radiomics for the identification of epidermal growth factor receptor …