Search Results for author: Evrim Turkbey

Found 12 papers, 1 papers with code

Improving Pneumonia Localization via Cross-Attention on Medical Images and Reports

no code implementations6 Oct 2021 Riddhish Bhalodia, Ali Hatamizadeh, Leo Tam, Ziyue Xu, Xiaosong Wang, Evrim Turkbey, Daguang Xu

Both the classification and localization are trained in conjunction and once trained, the model can be utilized for both the localization and characterization of pneumonia using only the input image.

Auto-FedAvg: Learnable Federated Averaging for Multi-Institutional Medical Image Segmentation

no code implementations20 Apr 2021 Yingda Xia, Dong Yang, Wenqi Li, Andriy Myronenko, Daguang Xu, Hirofumi Obinata, Hitoshi Mori, Peng An, Stephanie Harmon, Evrim Turkbey, Baris Turkbey, Bradford Wood, Francesca Patella, Elvira Stellato, Gianpaolo Carrafiello, Anna Ierardi, Alan Yuille, Holger Roth

In this work, we design a new data-driven approach, namely Auto-FedAvg, where aggregation weights are dynamically adjusted, depending on data distributions across data silos and the current training progress of the models.

Federated Learning Image Segmentation +3

Information Bottleneck Attribution for Visual Explanations of Diagnosis and Prognosis

no code implementations7 Apr 2021 Ugur Demir, Ismail Irmakci, Elif Keles, Ahmet Topcu, Ziyue Xu, Concetto Spampinato, Sachin Jambawalikar, Evrim Turkbey, Baris Turkbey, Ulas Bagci

We provide an innovative visual explanation algorithm for general purpose and as an example application, we demonstrate its effectiveness for quantifying lesions in the lungs caused by the Covid-19 with high accuracy and robustness without using dense segmentation labels.

Weakly supervised one-stage vision and language disease detection using large scale pneumonia and pneumothorax studies

1 code implementation31 Jul 2020 Leo K. Tam, Xiaosong Wang, Evrim Turkbey, Kevin Lu, Yuhong Wen, Daguang Xu

The architectural modifications address three obstacles -- implementing a supervised vision and language detection method in a weakly supervised fashion, incorporating clinical referring expression natural language information, and generating high fidelity detections with map probabilities.

Head Detection Referring Expression

DeepOrgan: Multi-level Deep Convolutional Networks for Automated Pancreas Segmentation

no code implementations22 Jun 2015 Holger R. Roth, Le Lu, Amal Farag, Hoo-chang Shin, Jiamin Liu, Evrim Turkbey, Ronald M. Summers

We propose and evaluate several variations of deep ConvNets in the context of hierarchical, coarse-to-fine classification on image patches and regions, i. e. superpixels.

Automated Pancreas Segmentation Computed Tomography (CT) +4

A Bottom-up Approach for Pancreas Segmentation using Cascaded Superpixels and (Deep) Image Patch Labeling

no code implementations22 May 2015 Amal Farag, Le Lu, Holger R. Roth, Jiamin Liu, Evrim Turkbey, Ronald M. Summers

We present a bottom-up approach for pancreas segmentation in abdominal CT scans that is based on a hierarchy of information propagation by classifying image patches at different resolutions; and cascading superpixels.

Computational Efficiency Organ Segmentation +4

A Bottom-Up Approach for Automatic Pancreas Segmentation in Abdominal CT Scans

no code implementations31 Jul 2014 Amal Farag, Le Lu, Evrim Turkbey, Jiamin Liu, Ronald M. Summers

Organ segmentation is a prerequisite for a computer-aided diagnosis (CAD) system to detect pathologies and perform quantitative analysis.

Clustering Computed Tomography (CT) +4

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