Review — An Efficient Deep Neural Network Based Abnormality Detection and Multi‑Class Breast Tumor Classification

BUS-CNN, VGG-19, and YOLOv3, are Evaluated

Breast Tumor Classification Datasets

An Efficient Deep Neural Network Based Abnormality Detection and Multi‑Class Breast Tumor Classification, BUS-CNN, by Dr. A.P.J.Abdul Kalam Technical University, 2022 JMTA (

Sik-Ho Tsang

@ Medium)
Medical Imaging, Medical Image Analysis, Image Classification

• Breast ultrasound image datasets are trained on 3 deep-learning architectures: BUS-CNN, VGG-19, and YOLOv3.
• YOLOv3 is found to be the best one.

Outline

1. Three Deep-Learning Architectures
2. Results

1. Three Deep-Learning Architectures

1.1. Framework

Framework

• Standard deep learning workflow is presented.
• The dataset is augmented, labeled and annotated. Then, it is split into training/validation/testing set. Then the training and validation sets are used for training the model. The testing set is used for evaluation.

1.2. Breast Ultrasound Convolution Neural Network (BUS-CNN)

Breast Ultrasound Convolution Neural Network (BUS-CNN)

• BUS-CNN consists of six convolutional layers and three max pooling layers.
• At the end, there are fully connected layers to sense the presence or absence of the breast tumor and its classification probability.

1.3. VGG-19

VGG-19

• VGG-19 is evaluated. (Please feel free to read VGG-19 if interested.)

1.4. YOLOv3

YOLO-v3

• YOLOv3 is evaluated. (Please feel free to read YOLOv3 if interested.)

2. Results

Receiver Operating Characteristics (ROC) of the trained deep learning models

• YOLOv3 obtains the best ROC curve.

Analysis of different CNN models

• YOLOv3 obtains the highest accuracy.

Though BUS-CNN is designed, VGG-19 and YOLOv3 are better.

Reference

[2022 JMTA] [BUS-CNN]
An Efficient Deep Neural Network Based Abnormality Detection and Multi‑Class Breast Tumor Classification

4.1. Biomedical Image Classification

2017 [ChestX-ray8] 2019 [CheXpert] 2020 [VGGNet for COVID-19] [Dermatology] 2021 [CheXternal] [CheXtransfer] 2022 [BUS-CNN]

My Other Previous Paper Readings