| P50 | author | Guro F. Giskeødegård | Q65706869 |
| | Tone F. Bathen | Q61104171 |
| P2093 | author name string | Peter Gibbs | |
| | Beathe Sitter | |
| | Martin D Pickles | |
| | Steinar Lundgren | |
| | Else Marie Huuse | |
| | Pål Erik Goa | |
| | Ioanna Chronaiou | |
| | Roja Hedayati | |
| | Jose Teruel | |
| P2860 | cites work | Evaluation of response to neoadjuvant chemoradiotherapy for locally advanced breast cancer with dynamic contrast-enhanced MRI of the breast | Q74829126 |
| | Texture analysis in assessment and prediction of chemotherapy response in breast cancer | Q85651409 |
| | Cancer statistics, 2019 | Q90941571 |
| | Dynamic breast MR imaging: are signal intensity time course data useful for differential diagnosis of enhancing lesions? | Q30572646 |
| | Texture analysis on MR images helps predicting non-response to NAC in breast cancer | Q35737991 |
| | Locally advanced breast cancer: MR imaging for prediction of response to neoadjuvant chemotherapy--results from ACRIN 6657/I-SPY TRIAL. | Q35985604 |
| | Assessing heterogeneity of lesion enhancement kinetics in dynamic contrast-enhanced MRI for breast cancer diagnosis | Q36323960 |
| | DCE-MRI analysis methods for predicting the response of breast cancer to neoadjuvant chemotherapy: pilot study findings | Q37093041 |
| | Dynamic contrast-enhanced MRI in the diagnosis and management of breast cancer | Q37226656 |
| | Dynamic contrast-enhanced MRI-based biomarkers of therapeutic response in triple-negative breast cancer | Q37292720 |
| | Classification of small lesions in dynamic breast MRI: Eliminating the need for precise lesion segmentation through spatio-temporal analysis of contrast enhancement over time | Q37305321 |
| | Diagnosis of breast masses from dynamic contrast-enhanced and diffusion-weighted MR: a machine learning approach. | Q37538876 |
| | Neoadjuvant Chemotherapy Creates Surgery Opportunities For Inoperable Locally Advanced Breast Cancer | Q37714871 |
| | Meta-analysis confirms achieving pathological complete response after neoadjuvant chemotherapy predicts favourable prognosis for breast cancer patients | Q37898842 |
| | Gadolinium contrast agents for CNS imaging: current concepts and clinical evidence | Q38213840 |
| | Intratumor partitioning and texture analysis of dynamic contrast-enhanced (DCE)-MRI identifies relevant tumor subregions to predict pathological response of breast cancer to neoadjuvant chemotherapy | Q38808843 |
| | Texture analysis of medical images for radiotherapy applications | Q39019381 |
| | Prognostic value DCE-MRI parameters in predicting factor disease free survival and overall survival for breast cancer patients | Q43682028 |
| | Monitoring the size and response of locally advanced breast cancers to neoadjuvant chemotherapy (weekly paclitaxel and epirubicin) with serial enhanced MRI. | Q44335697 |
| | REporting recommendations for tumor MARKer prognostic studies (REMARK). | Q46099462 |
| | Radiomics: the bridge between medical imaging and personalized medicine | Q47869134 |
| | Can algorithmically assessed MRI features predict which patients with a preoperative diagnosis of ductal carcinoma in situ are upstaged to invasive breast cancer? | Q47978876 |
| | Quantitative DCE-MRI for prediction of pathological complete response following neoadjuvant treatment for locally advanced breast cancer: the impact of breast cancer subtypes on the diagnostic accuracy. | Q48141719 |
| | Parkinson's disease: interhemispheric textural differences in MR images | Q49017632 |
| | Influence of MRI acquisition protocols and image intensity normalization methods on texture classification. | Q51030226 |
| | Characterization of spatiotemporal changes for the classification of dynamic contrast-enhanced magnetic-resonance breast lesions. | Q51237420 |
| | Breast Cancer Heterogeneity: MR Imaging Texture Analysis and Survival Outcomes. | Q51783103 |
| | Effects of MRI acquisition parameter variations and protocol heterogeneity on the results of texture analysis and pattern discrimination: an application-oriented study. | Q51827133 |
| | Volumetric texture analysis of breast lesions on contrast-enhanced magnetic resonance images. | Q51906898 |
| | Neoadjuvant and adjuvant trastuzumab in patients with HER2-positive locally advanced breast cancer (NOAH): follow-up of a randomised controlled superiority trial with a parallel HER2-negative cohort | Q57579888 |
| | Locally advanced breast cancer treated with neoadjuvant chemotherapy and adjuvant radiotherapy: a retrospective cohort analysis | Q64078824 |
| P304 | page(s) | 284185119885116 | |
| P577 | publication date | 2019-11-19 | |
| P1433 | published in | Acta Radiologica | Q4033350 |
| P1476 | title | Feasibility of contrast-enhanced MRI derived textural features to predict overall survival in locally advanced breast cancer | |