A Gradient Mapping Guided Explainable Deep Neural Network for Extracapsular Extension Identification in 3D Head and Neck Cancer Computed Tomography Images

01/03/2022
by   Yibin Wang, et al.
11

Diagnosis and treatment management for head and neck squamous cell carcinoma (HNSCC) is guided by routine diagnostic head and neck computed tomography (CT) scans to identify tumor and lymph node features. Extracapsular extension (ECE) is a strong predictor of patients' survival outcomes with HNSCC. It is essential to detect the occurrence of ECE as it changes staging and management for the patients. Current clinical ECE detection relies on visual identification and pathologic confirmation conducted by radiologists. Machine learning (ML)-based ECE diagnosis has shown high potential in the recent years. However, manual annotation of lymph node region is a required data preprocessing step in most of the current ML-based ECE diagnosis studies. In addition, this manual annotation process is time-consuming, labor-intensive, and error-prone. Therefore, in this paper, we propose a Gradient Mapping Guided Explainable Network (GMGENet) framework to perform ECE identification automatically without requiring annotated lymph node region information. The gradient-weighted class activation mapping (Grad-CAM) technique is proposed to guide the deep learning algorithm to focus on the regions that are highly related to ECE. Informative volumes of interest (VOIs) are extracted without labeled lymph node region information. In evaluation, the proposed method is well-trained and tested using cross validation, achieving test accuracy and AUC of 90.2 analyzed and correlated with gold standard histopathological findings.

READ FULL TEXT

page 13

page 18

page 19

research
10/26/2021

A Precision Diagnostic Framework of Renal Cell Carcinoma on Whole-Slide Images using Deep Learning

Diagnostic pathology, which is the basis and gold standard of cancer dia...
research
09/06/2021

Automatic Segmentation of the Optic Nerve Head Region in Optical Coherence Tomography: A Methodological Review

The optic nerve head represents the intraocular section of the optic ner...
research
05/31/2023

Diagnosis and Prognosis of Head and Neck Cancer Patients using Artificial Intelligence

Cancer is one of the most life-threatening diseases worldwide, and head ...
research
01/17/2022

Automatic Segmentation of Head and Neck Tumor: How Powerful Transformers Are?

Cancer is one of the leading causes of death worldwide, and head and nec...
research
01/09/2023

Integrating features from lymph node stations for metastatic lymph node detection

Metastasis on lymph nodes (LNs), the most common way of spread for prima...
research
06/20/2022

Metareview-informed Explainable Cytokine Storm Detection during CAR-T cell Therapy

Cytokine release syndrome (CRS), also known as cytokine storm, is one of...

Please sign up or login with your details

Forgot password? Click here to reset