Search Results for author: Douglas P. S. Gomes

Found 5 papers, 3 papers with code

Improved Abdominal Multi-Organ Segmentation via 3D Boundary-Constrained Deep Neural Networks

1 code implementation9 Oct 2022 Samra Irshad, Douglas P. S. Gomes, Seong Tae Kim

To address the problem of abdominal multi-organ segmentation, we train the 3D encoder-decoder network to simultaneously segment the abdominal organs and their corresponding boundaries in CT scans via multi-task learning.

Image Segmentation Medical Image Segmentation +4

VeHIF: An Accessible Vegetation High-Impedance Fault Data Set Format

1 code implementation7 Dec 2021 Douglas P. S. Gomes, Cagil Ozansoy

The current research field dedicated to studying these faults is extensive but suffers from a constraining bottleneck of a lack of real experimental data.

Vocal Bursts Intensity Prediction

Deep Mining Generation of Lung Cancer Malignancy Models from Chest X-ray Images

no code implementations10 Dec 2020 Michael J. Horry, Subrata Chakraborty, Biswajeet Pradhan, Manoranjan Paul, Douglas P. S. Gomes, Anwaar Ul-Haq

Decision trees mined using this method may be considered as a starting point for refinement into clinically useful multi-variate lung cancer malignancy models for implementation as a workflow augmentation tool to improve the efficiency of human radiologists.

Lung Nodule Detection Specificity

MAVIDH Score: A COVID-19 Severity Scoring using Chest X-Ray Pathology Features

1 code implementation30 Nov 2020 Douglas P. S. Gomes, Michael J. Horry, Anwaar Ulhaq, Manoranjan Paul, Subrata Chakraborty, Manash Saha, Tanmoy Debnath, D. M. Motiur Rahaman

As the primary contribution, this method correlates well to patient severity in different stages of disease progression with competitive results compared to other existing, more complex methods.

COVID-19 Diagnosis

Potential Features of ICU Admission in X-ray Images of COVID-19 Patients

no code implementations26 Sep 2020 Douglas P. S. Gomes, Anwaar Ulhaq, Manoranjan Paul, Michael J. Horry, Subrata Chakraborty, Manas Saha, Tanmoy Debnath, D. M. Motiur Rahaman

X-ray images may present non-trivial features with predictive information of patients that develop severe symptoms of COVID-19.

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