@inproceedings{06ba525c6fe14796a71460cabf1b17d3,
title = "Cascaded Networks for Thyroid Nodule Diagnosis from Ultrasound Images",
abstract = "Computer-aided diagnostics (CAD) based on deep learning methods have grown to be the most concerned method in recent years due to its safety, efficiency and economy. CAD{\textquoteright}s function varies from providing second opinion to doctors to establishing a baseline upon which further diagnostics can be conducted [3]. In this paper, we cross-compare different approaches to classify thyroid nodules and finally propose a method that can exploit interaction between segmentation and classification task. In our method, detection and segmentation results are combined to produce class-discriminative clues for boosting classification performance. Our method is applied to TN-SCUI 2020, a MICCAI 2020 challenge and achieved third place in classification task. In this paper, we provide exhaustive empirical evidence to demonstrate the applicability and efficacy of our method.",
keywords = "Classification, Detection, Segmentation, Thyroid nodule, Ultrasound images",
author = "Xueda Shen and Xi Ouyang and Tianjiao Liu and Dinggang Shen",
note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; Anatomical Brain Barriers to Cancer Spread: Segmentation from CT and MR Images Challenge, ABCs 2020, Learn2Reg Challenge, L2R 2020 and Thyroid Nodule Segmentation and Classification in Ultrasound Images Challenge, TN-SCUI 2020 held in conjunction with 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020 ; Conference date: 04-10-2020 Through 08-10-2020",
year = "2021",
doi = "10.1007/978-3-030-71827-5_19",
language = "English",
isbn = "9783030718268",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "145--154",
editor = "Nadya Shusharina and Heinrich, {Mattias P.} and Ruobing Huang",
booktitle = "Segmentation, Classification, and Registration of Multi-modality Medical Imaging Data - MICCAI 2020 Challenges, ABCs 2020, L2R 2020, TN-SCUI 2020, Held in Conjunction with MICCAI 2020, Proceedings",
address = "Germany",
}