Multi-Task Lung Nodule Detection in Chest Radiographs with a Dual Head Network

• URL: http://arxiv.org/abs/2207.03050v1
• Date: Thu, 7 Jul 2022 02:29:34 GMT
• Title: Multi-Task Lung Nodule Detection in Chest Radiographs with a Dual Head Network
• Authors: Chen-Han Tsai, Yu-Shao Peng
• Abstract summary: Lung nodules can be an alarming precursor to potential lung cancer. Missed nodule detections during chest radiograph analysis remains a common challenge. We present a multi-task lung nodule detection algorithm for chest radiograph analysis.
• Score: 0.7614628596146599
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Lung nodules can be an alarming precursor to potential lung cancer. Missed nodule detections during chest radiograph analysis remains a common challenge among thoracic radiologists. In this work, we present a multi-task lung nodule detection algorithm for chest radiograph analysis. Unlike past approaches, our algorithm predicts a global-level label indicating nodule presence along with local-level labels predicting nodule locations using a Dual Head Network (DHN). We demonstrate the favorable nodule detection performance that our multi-task formulation yields in comparison to conventional methods. In addition, we introduce a novel Dual Head Augmentation (DHA) strategy tailored for DHN, and we demonstrate its significance in further enhancing global and local nodule predictions.

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