no code implementations • 17 Apr 2024 • Fakrul Islam Tushar, Liesbeth Vancoillie, Cindy McCabe, Amareswararao Kavuri, Lavsen Dahal, Brian Harrawood, Milo Fryling, Mojtaba Zarei, Saman Sotoudeh-Paima, Fong Chi Ho, Dhrubajyoti Ghosh, Sheng Luo, W. Paul Segars, Ehsan Abadi, Kyle J. Lafata, Ehsan Samei, Joseph Y. Lo
Objectives: To establish a virtual imaging trial (VIT) platform that accurately simulates real-world lung screening trials (LSTs) to assess the diagnostic accuracy of CT and CXR modalities.
1 code implementation • 6 Feb 2024 • Fakrul Islam Tushar, Vincent M. D'Anniballe, Geoffrey D. Rubin, Joseph Y. Lo
First, we examined model tolerance for noisy data by incrementally increasing error in the labels within the training data.
1 code implementation • 17 Aug 2023 • Fakrul Islam Tushar, Lavsen Dahal, Saman Sotoudeh-Paima, Ehsan Abadi, W. Paul Segars, Ehsan Samei, Joseph Y. Lo
In this study, COVID-19 serves as a case example to unveil the intrinsic and extrinsic factors influencing AI performance.
no code implementations • 7 Mar 2022 • Fakrul Islam Tushar, Ehsan Abadi, Saman Sotoudeh-Paima, Rafael B. Fricks, Maciej A. Mazurowski, W. Paul Segars, Ehsan Samei, Joseph Y. Lo
However, performance dropped to an AUC of 0. 65 and 0. 69 when evaluated on clinical and our simulated CVIT-COVID dataset.
no code implementations • 3 Mar 2022 • Fakrul Islam Tushar, Husam Nujaim, Wanyi Fu, Ehsan Abadi, Maciej A. Mazurowski, Ehsan Samei, William P. Segars, Joseph Y. Lo
This demonstrates that quality data is the key to improving the model's performance.
no code implementations • 23 Feb 2022 • Fakrul Islam Tushar, Vincent M. D'Anniballe, Geoffrey D. Rubin, Ehsan Samei, Joseph Y. Lo
Despite the potential of weakly supervised learning to automatically annotate massive amounts of data, little is known about its limitations for use in computer-aided diagnosis (CAD).
1 code implementation • 5 Feb 2021 • Vincent M. D'Anniballe, Fakrul Islam Tushar, Khrystyna Faryna, Songyue Han, Maciej A. Mazurowski, Geoffrey D. Rubin, Joseph Y. Lo
Pre-trained models outperformed random initialization across all diseases.
1 code implementation • 3 Aug 2020 • Fakrul Islam Tushar, Vincent M. D'Anniballe, Rui Hou, Maciej A. Mazurowski, Wanyi Fu, Ehsan Samei, Geoffrey D. Rubin, Joseph Y. Lo
Purpose: To design multi-disease classifiers for body CT scans for three different organ systems using automatically extracted labels from radiology text reports. Materials & Methods: This retrospective study included a total of 12, 092 patients (mean age 57 +- 18; 6, 172 women) for model development and testing (from 2012-2017).
2 code implementations • 9 Jul 2019 • Md. Kamrul Hasan, Lavsen Dahal, Prasad N. Samarakoon, Fakrul Islam Tushar, Robert Marti Marly
We evaluate our proposed model on two publicly available datasets, namely ISIC-2017 and PH2.
no code implementations • 5 Apr 2019 • Md. Kamrul Hasan, Basel Alyafi, Fakrul Islam Tushar
The contribution of this paper is to present and compare two different approaches to skin lesion segmentation.
1 code implementation • 29 Mar 2019 • Fakrul Islam Tushar, Basel Alyafi, Md. Kamrul Hasan, Lavsen Dahal
The outcome of the research indicates that for the IBSR18 data-set, pre-processing and proper tuning of hyper-parameters for NeuroNet model have improvement in DSC for the brain tissue segmentation.
1 code implementation • 30 Sep 2018 • Md. Kamrul Hasan, Fakrul Islam Tushar
For analysis cardiac functionality, extracting information from the Left ventricular (LV) is already a broad field of Medical Imaging.
1 code implementation • 30 Sep 2018 • Fakrul Islam Tushar
Skin lesion segmentation is one of the first steps towards automatic Computer-Aided Diagnosis of skin cancer.