activity
20212024
most citedDeepDoseNet: A Deep Learning model for 3D Dose Prediction in Radiation Therapy

1 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

physics.med-ph2024

Divergent Clinical Equivalence Findings from DVH and NTCP Metrics for Alternative OAR Delineations with Increasing Setup Variability in Head-and-Neck Radiotherapy

M. N. H. Rashad, Abishek Karki, Jason Czak +4

Purpose: This study quantifies the variation in dose-volume histogram (DVH) and normal tissue complication probability (NTCP) metrics for head-and-neck (HN) cancer patients when al…

physics.med-ph2022★ 1 cited

OpenKBP-Opt: An international and reproducible evaluation of 76 knowledge-based planning pipelines

Aaron Babier, Rafid Mahmood, Binghao Zhang +56

We establish an open framework for developing plan optimization models for knowledge-based planning (KBP) in radiotherapy. Our framework includes reference plans for 100 patients w…

physics.med-ph2021

Gross patient error detection via cine transmission dosimetry

Nguyen Phuong Dang, Victor Gabriel Leandro Alves, Mahmoud Ahmed +1

To quantify the effectiveness of EPID-based cine transmission dosimetry to detect gross patient anatomic errors. EPID image fra…

physics.med-ph2021★ 1 cited

DeepDoseNet: A Deep Learning model for 3D Dose Prediction in Radiation Therapy

Mumtaz Hussain Soomro, Victor Gabriel Leandro Alves, Hamidreza Nourzadeh +1

The DeepDoseNet 3D dose prediction model based on ResNet and Dilated DenseNet is proposed. The 340 head-and-neck datasets from the 2020 AAPM OpenKBP challenge were utilized, with 2…

eess.IV2021★ 1 cited

OARnet: Automated organs-at-risk delineation in Head and Neck CT images

Mumtaz Hussain Soomro, Hamidreza Nourzadeh, Victor Gabriel Leandro Alves +2

A 3D deep learning model (OARnet) is developed and used to delineate 28 H&N OARs on CT images. OARnet utilizes a densely connected network to detect the OAR bounding-box, then deli…