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Abhinay Krishna Vellala
Abhinay Krishna Vellala
Medical Computer Scientist
在 medma.uni-heidelberg.de 的电子邮件经过验证
标题
引用次数
引用次数
年份
Tumor classification of gastrointestinal liver metastases using CT-based radiomics and deep learning
H Tharmaseelan, AK Vellala, A Hertel, F Tollens, LT Rotkopf, J Rink, ...
Cancer Imaging 23 (1), 95, 2023
122023
MRI imaging and machine learning based radiomics for detection of mixed HCC and CCA tumors: Still a need for liver biopsy?
Y Qian, Q Lu, I Rodriguez, M Vácha, X Min, MR Ümütlü, GA Castrillon, ...
Journal of Clinical Oncology 43 (4_suppl), 531-531, 2025
2025
Radiomics-based prediction of HCC response to atezolizumab/bevacizumab.
I Rodriguez, A Vellala, T Itzel, M Vácha, DH Chang, M Dill, ...
Journal of Clinical Oncology 43 (4_suppl), 636-636, 2025
2025
Radiomics-driven spectral profiling of six kidney stone types with monoenergetic CT reconstructions in photon-counting CT
A Hertel, MF Froelich, D Overhoff, T Nestler, S Faby, M Jürgens, ...
European Radiology, 1-11, 2024
2024
Textural heterogeneity of liver lesions in CT imaging: comparison of colorectal and pancreatic metastases: hepatobiliary
FL Pietsch, F Haag, I Ayx, F Grawe, AK Vellala, S Schönberg, MF Froelich, ...
2024
Textural heterogeneity of liver lesions in CT imaging-comparison of colorectal and pancreatic metastases
FL Pietsch, F Haag, I Ayx, F Grawe, AK Vellala, SO Schoenberg, ...
Abdominal Radiology 49 (12), 4295-4306, 2024
2024
Radiomics-based prediction of HCC response to atezolizumab/bevacizumab
I Rodriguez, A Vellala, T Itzel, J Daza, M Vácha, DH Chang, M Debic, ...
Zeitschrift für Gastroenterologie 62 (09), KV 249, 2024
2024
Comparing quantitative image parameters between animal and clinical CT-scanners: a translational phantom study analysis
A Vellala, C Mogler, F Haag, F Tollens, H Rudolf, F Pietsch, C Wängler, ...
Frontiers in Medicine 11, 1407235, 2024
2024
1st. Joint DFH/UFA workshop on AI in Medicine: Optimised Trials with Machine Learning
X Fresquet, J Hesser
Heidelberg University Library, 2024
2024
Genre-based Video Clustering using Deep Learning: By Extraction feature using Object Detection and Action Recognition
A Vellala
2021
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