An original voxel-wise supervised analysis of tumors with multimodal radiomics to highlight predictive biological patterns
T Escobar, S Vauclin, F Orlhac, C Nioche, P Pineau… - 2021 - Soc Nuclear Med
1404 Objectives: Translational applications of predictive and prognostic image-based
learning models are challenging due to their lack of interpretability. When using deep …
learning models are challenging due to their lack of interpretability. When using deep …
Voxel‐wise supervised analysis of tumors with multimodal engineered features to highlight interpretable biological patterns
T Escobar, S Vauclin, F Orlhac, C Nioche… - Medical …, 2022 - Wiley Online Library
Background Translation of predictive and prognostic image‐based learning models to
clinical applications is challenging due in part to their lack of interpretability. Some deep …
clinical applications is challenging due in part to their lack of interpretability. Some deep …
Responsible radiomics research for faster clinical translation
M Vallières, A Zwanenburg, B Badic… - Journal of Nuclear …, 2018 - Soc Nuclear Med
It is now recognized that intratumoral heterogeneity is associated with more aggressive
tumor phenotypes leading to poor patient outcomes (1). Medical imaging plays a central role …
tumor phenotypes leading to poor patient outcomes (1). Medical imaging plays a central role …
A multi-modality radiomics-based model for predicting recurrence in non-small cell lung cancer
JR Christie, M Abdelrazek, P Lang… - Medical Imaging …, 2021 - spiedigitallibrary.org
Non-small cell lung cancer (NSCLC) is one of the leading causes of death worldwide.
Medical imaging is used to determine cancer staging; however, these images may hold …
Medical imaging is used to determine cancer staging; however, these images may hold …
Multiple machine learning algorithms for overall survival modeling of NSCLC patients using PET-, CT-, and fusion-based radiomics
1192 Objectives: Multi-modality radiomics-guided prognostic models proved to have a
promising potential towards precision oncology. It enhances the prognostic performance …
promising potential towards precision oncology. It enhances the prognostic performance …
Predicting recurrence risks in lung cancer patients using multimodal radiomics and random survival forests
JR Christie, O Daher, M Abdelrazek… - Journal of Medical …, 2022 - spiedigitallibrary.org
Purpose We developed a model integrating multimodal quantitative imaging features from
tumor and nontumor regions, qualitative features, and clinical data to improve the risk …
tumor and nontumor regions, qualitative features, and clinical data to improve the risk …
Training of deep convolutional neural nets to extract radiomic signatures of tumors
406 Objectives: Radiomics-based analysis of FDG PET images has been shown to improve
the assessment and prediction of tumor growth rate, response to treatment and other patient …
the assessment and prediction of tumor growth rate, response to treatment and other patient …
PET-CT Fusion Based Outcome Prediction in Lung Cancer using Deep and Handcrafted Radiomics Features and Machine Learning
P1196 Introduction: Although the use of hand-crafted radiomics features (RF) has shown
significant promise to improve diagnostic, prognostic, and treatment response assessments …
significant promise to improve diagnostic, prognostic, and treatment response assessments …
[HTML][HTML] A comparative study of radiomics and deep-learning based methods for pulmonary nodule malignancy prediction in low dose CT images
Objectives: Both radiomics and deep learning methods have shown great promise in
predicting lesion malignancy in various image-based oncology studies. However, it is still …
predicting lesion malignancy in various image-based oncology studies. However, it is still …
[HTML][HTML] The role of deep learning and radiomic feature extraction in cancer-specific predictive modelling: a review
This paper reviews objective methods for prognostic modelling of cancer tumours located
within radiology images, a process known as radiomics. Radiomics is a novel feature …
within radiology images, a process known as radiomics. Radiomics is a novel feature …