Impact of image quality on radiomics applications
Y Cui, FF Yin - Physics in Medicine & Biology, 2022 - iopscience.iop.org
Radiomics features extracted from medical images have been widely reported to be useful
in the patient specific outcome modeling for variety of assessment and prediction purposes …
in the patient specific outcome modeling for variety of assessment and prediction purposes …
Radiomics-based machine learning models to distinguish between metastatic and healthy bone using lesion-center-based geometric regions of interest
Radiomics-based machine learning classifiers have shown potential for detecting bone
metastases (BM) and for evaluating BM response to radiotherapy (RT). However, current …
metastases (BM) and for evaluating BM response to radiotherapy (RT). However, current …
The effect of harmonization on the variability of PET radiomic features extracted using various segmentation methods
Purpose This study aimed to examine the robustness of positron emission tomography
(PET) radiomic features extracted via different segmentation methods before and after …
(PET) radiomic features extracted via different segmentation methods before and after …
Prognosis Prediction of Diffuse Large B-cell Lymphoma in F-FDG PET images Based on Multi-Deep-Learning Models
C Qian, C Jiang, K Xie, C Ding, Y Teng… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
Diffuse large B-cell lymphoma (DLBCL), a cancer of B cells, has been one of the most
challenging and complicated diseases because of its considerable variation in clinical …
challenging and complicated diseases because of its considerable variation in clinical …
Classifying Malignancy in Prostate Glandular Structures from Biopsy Scans with Deep Learning
Simple Summary In recent years, the prostate cancer histopathological description proposed
by Gleason has emerged as a universal standard used for disease diagnosis and …
by Gleason has emerged as a universal standard used for disease diagnosis and …
A radiomics-based machine learning pipeline to distinguish between metastatic and healthy bone using lesion-center-based geometric regions of interest
Radiomics-based machine learning classifiers have shown potential for detecting bone
metastases (BM) and for evaluating BM response to radiotherapy (RT). However, current …
metastases (BM) and for evaluating BM response to radiotherapy (RT). However, current …
Radiomics for differentiation of the posterior fossa pilocytic astrocytoma versus hemangioblastomas in adults. A pilot study
Purpose Both pilocytic astrocytoma (PA) and hemangioblastoma (HB) are common primary
neoplasms of the posterior fossa with similar radiological manifestations. This study was …
neoplasms of the posterior fossa with similar radiological manifestations. This study was …
SPIE Computer-Aided Diagnosis conference anniversary review
RM Summers, ML Giger - Journal of Medical Imaging, 2022 - spiedigitallibrary.org
The SPIE Computer-Aided Diagnosis conference has been held for 16 consecutive years at
the annual SPIE Medical Imaging symposium. The conference remains vibrant, with a core …
the annual SPIE Medical Imaging symposium. The conference remains vibrant, with a core …
[PDF][PDF] Predicting Tumour Response with Radiomics and Machine Learning in MR-Guided Cervix Brachytherapy
R Bellis - 2022 - rshare.library.torontomu.ca
This study seeks to determine if radiomic features extracted from whole or part of the gross
tumour volume of locally advanced cervical cancer (LACC) patients can be used to predict …
tumour volume of locally advanced cervical cancer (LACC) patients can be used to predict …