Search Results for author: Fakrul Islam Tushar

Found 10 papers, 6 papers with code

Co-occurring Diseases Heavily Influence the Performance of Weakly Supervised Learning Models for Classification of Chest CT

no code implementations23 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).

Classification Multi-Label Classification

Classification of Multiple Diseases on Body CT Scans using Weakly Supervised Deep Learning

1 code implementation3 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).

Computed Tomography (CT) General Classification

Brain Tissue Segmentation Using NeuroNet With Different Pre-processing Techniques

1 code implementation29 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.

3D Semantic Segmentation

Automatic Skin Lesion Segmentation Using GrabCut in HSV Colour Space

1 code implementation30 Sep 2018 Fakrul Islam Tushar

Skin lesion segmentation is one of the first steps towards automatic Computer-Aided Diagnosis of skin cancer.

Lesion Segmentation Skin Lesion Segmentation

Quantification of Trabeculae Inside the Heart from MRI Using Fractal Analysis

1 code implementation30 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.

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