no code implementations • 28 Dec 2023 • Taha Emre, Arunava Chakravarty, Antoine Rivail, Dmitrii Lachinov, Oliver Leingang, Sophie Riedl, Julia Mai, Hendrik P. N. Scholl, Sobha Sivaprasad, Daniel Rueckert, Andrew Lotery, Ursula Schmidt-Erfurth, Hrvoje Bogunović
Self-supervised learning (SSL) has emerged as a powerful technique for improving the efficiency and effectiveness of deep learning models.
no code implementations • 25 Jul 2023 • Taha Emre, Marzieh Oghbaie, Arunava Chakravarty, Antoine Rivail, Sophie Riedl, Julia Mai, Hendrik P. N. Scholl, Sobha Sivaprasad, Daniel Rueckert, Andrew Lotery, Ursula Schmidt-Erfurth, Hrvoje Bogunović
In the field of medical imaging, 3D deep learning models play a crucial role in building powerful predictive models of disease progression.
no code implementations • 17 Apr 2023 • Arunava Chakravarty, Taha Emre, Oliver Leingang, Sophie Riedl, Julia Mai, Hendrik P. N. Scholl, Sobha Sivaprasad, Daniel Rueckert, Andrew Lotery, Ursula Schmidt-Erfurth, Hrvoje Bogunović
We develop a Deep Learning (DL) model to predict the future risk of conversion of an eye from iAMD to nAMD from its current OCT scan.
no code implementations • 8 Nov 2022 • Dmitrii Lachinov, Arunava Chakravarty, Christoph Grechenig, Ursula Schmidt-Erfurth, Hrvoje Bogunovic
Our method represents a time-invariant physical process and solves a large-scale problem of modeling temporal pixel-level changes utilizing NeuralODEs.
1 code implementation • 30 Jun 2022 • Taha Emre, Arunava Chakravarty, Antoine Rivail, Sophie Riedl, Ursula Schmidt-Erfurth, Hrvoje Bogunović
Recent contrastive learning methods achieved state-of-the-art in low label regimes.
no code implementations • 24 Apr 2020 • Arka Mitra, Arunava Chakravarty, Nirmalya Ghosh, Tandra Sarkar, Ramanathan Sethuraman, Debdoot Sheet
Chest radiographs are primarily employed for the screening of pulmonary and cardio-/thoracic conditions.
no code implementations • 24 Apr 2020 • Arunava Chakravarty, Tandra Sarkar, Nirmalya Ghosh, Ramanathan Sethuraman, Debdoot Sheet
Chest radiographs are primarily employed for the screening of cardio, thoracic and pulmonary conditions.
no code implementations • 24 Apr 2020 • Sarath Chandra K, Arunava Chakravarty, Nirmalya Ghosh, Tandra Sarkar, Ramanathan Sethuraman, Debdoot Sheet
Our method performed well on the task of localization of masses with an average Precision/Recall of 0. 76/0. 80 and acheived an average AUC of 0. 91 on the imagelevel classification task using a five-fold cross-validation on the INbreast dataset.