Transformers in medical imaging: A survey
Following unprecedented success on the natural language tasks, Transformers have been
successfully applied to several computer vision problems, achieving state-of-the-art results …
successfully applied to several computer vision problems, achieving state-of-the-art results …
[HTML][HTML] Radiomics and artificial intelligence for precision medicine in lung cancer treatment
Lung cancer is the leading cause of cancer-related deaths worldwide. It exhibits, at the
mesoscopic scale, phenotypic characteristics that are generally indiscernible to the human …
mesoscopic scale, phenotypic characteristics that are generally indiscernible to the human …
A large annotated medical image dataset for the development and evaluation of segmentation algorithms
Semantic segmentation of medical images aims to associate a pixel with a label in a medical
image without human initialization. The success of semantic segmentation algorithms is …
image without human initialization. The success of semantic segmentation algorithms is …
Radiomics for survival risk stratification of clinical and pathologic stage IA pure-solid non–small cell lung cancer
Background Radiomics-based biomarkers enable the prognostication of resected non–small
cell lung cancer (NSCLC), but their effectiveness in clinical stage and pathologic stage IA …
cell lung cancer (NSCLC), but their effectiveness in clinical stage and pathologic stage IA …
Machine learning-based radiomics signatures for EGFR and KRAS mutations prediction in non-small-cell lung cancer
Early identification of epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma viral
oncogene homolog (KRAS) mutations is crucial for selecting a therapeutic strategy for …
oncogene homolog (KRAS) mutations is crucial for selecting a therapeutic strategy for …
Generalized ComBat harmonization methods for radiomic features with multi-modal distributions and multiple batch effects
Radiomic features have a wide range of clinical applications, but variability due to image
acquisition factors can affect their performance. The harmonization tool ComBat is a …
acquisition factors can affect their performance. The harmonization tool ComBat is a …
[HTML][HTML] Data preparation for artificial intelligence in medical imaging: A comprehensive guide to open-access platforms and tools
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 …
professionals to turn to novel technologies in order to efficiently handle their data and exploit …
[HTML][HTML] Impact of feature harmonization on radiogenomics analysis: Prediction of EGFR and KRAS mutations from non-small cell lung cancer PET/CT images
Objective To investigate the impact of harmonization on the performance of CT, PET, and
fused PET/CT radiomic features toward the prediction of mutations status, for epidermal …
fused PET/CT radiomic features toward the prediction of mutations status, for epidermal …
[HTML][HTML] A review of original articles published in the emerging field of radiomics
J Song, Y Yin, H Wang, Z Chang, Z Liu, L Cui - European journal of …, 2020 - Elsevier
Purpose To determine the characteristics of and trends in research in the emerging field of
radiomics through bibliometric and hotspot analyses of relevant original articles published …
radiomics through bibliometric and hotspot analyses of relevant original articles published …
Clinical validation of deep learning algorithms for radiotherapy targeting of non-small-cell lung cancer: an observational study
Background Artificial intelligence (AI) and deep learning have shown great potential in
streamlining clinical tasks. However, most studies remain confined to in silico validation in …
streamlining clinical tasks. However, most studies remain confined to in silico validation in …