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TAO TAN
Associate Professor
Associate Professor
,
Faculty of Applied Sciences
Phone
8599 6643
Email
taotan
mpu.edu
mo
h-index
2259
Citations
24
h-index
Calculated based on number of publications stored in Pure and citations from Scopus
2011
2025
Research activity per year
Overview
Fingerprint
Network
Research Output
(142)
Press/Media
(30)
Similar Profiles
(6)
Fingerprint
Dive into the research topics where TAO TAN is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Computer Science
Convolutional Neural Network
100%
Deep Learning Method
96%
Ultrasound Image
70%
Feature Extraction
57%
Experimental Result
50%
Computer Aided Detection
47%
Image Segmentation
46%
Artificial Intelligence
46%
Annotation
36%
Imaging Modality
32%
Segmentation Method
30%
False Positive
29%
U-Net
28%
Image Analysis
27%
Deep Neural Network
27%
Superior Performance
25%
Attention (Machine Learning)
24%
Artificial Intelligence Model
24%
Characteristic Curve
23%
Support Vector Machine
20%
Clinical Application
19%
Dynamic Programming
19%
Classification Performance
18%
Medical Imaging
17%
Image Classification
17%
de-noising
16%
YOLOv5
16%
Image Similarity
16%
Feature Selection
16%
Large Language Model
16%
Classification Algorithm
16%
super resolution
16%
Lesion Segmentation
15%
Local Information
15%
Contextual Information
14%
Programming Method
14%
local feature
13%
Global Information
13%
Fold Cross Validation
13%
Segmentation Model
13%
Learning Framework
12%
Learning Approach
12%
Leaning Parameter
12%
Semantic Feature
11%
Neural Network
11%
Deep Convolutional Neural Networks
11%
Object Detection
10%
Detection Method
10%
Clinical Setting
10%
Linear Discriminant Analysis
10%
Medicine and Dentistry
Breast Ultrasound
82%
Breast Cancer
73%
Cancer Diagnosis
34%
Malignant Neoplasm
33%
Diagnosis
32%
Mammography
24%
Magnetic Resonance Imaging
22%
Lung Cancer
17%
Diseases
16%
Breast Imaging
16%
Non-Alcoholic Fatty Liver Disease
16%
COVID-19
16%
Digital Mammography
15%
Radiation Therapy
14%
Computer Assisted Tomography
13%
Transfer of Learning
13%
Feature Extraction
12%
Maturity Onset Diabetes of the Young
12%
Radiomics
12%
False Positive Result
12%
Intensity Modulated Radiation Therapy
11%
Diagnostic Performance
11%
Clinician
10%
Lung
10%
Nonalcoholic Fatty Liver
10%
Computer-Aided Diagnosis
9%
Cardiovascular Disease
9%
Patient Population
9%
Retinopathy of Prematurity
8%
Bleeding
8%
Radiation Therapy Planning
8%
Retina Image
8%
Neck
8%
Chronic Kidney Disease
8%
Breast Tumor
8%
Digital Subtraction Angiography
8%
Stomach Mucosa
8%
MALT Lymphoma
8%
Histopathology
8%
Neurinoma
8%
Breast Disease
8%
Electronic Health Record
8%
Decision Making
8%
Cancer Classification
8%
Artery Occlusion
8%
Emphysema
8%
Impaired Glucose Tolerance
8%
Hemoglobin A1c
8%
Vestibular Schwannoma
8%
Retinal Arteriole
8%
Engineering
Deep Learning Method
69%
Convolutional Neural Network
55%
Experimental Result
51%
Multiscale
19%
Feature Extraction
19%
Segmentation Method
18%
Radiotherapy
16%
Computer Aided Detection
16%
Phase Classification
16%
Facial Expression
16%
Joints (Structural Components)
16%
State-of-the-Art Method
16%
Support Vector Machine
16%
Similarities
14%
Imaging Modality
12%
Body Motion
12%
Speckle
12%
Radiologist
12%
Artificial Intelligence
11%
Metrics
11%
Classification Performance
10%
Gaussians
10%
Image Reconstruction
10%
Level Semantics
9%
Learning Approach
9%
Local Information
8%
Image Classification
8%
Loss Function
8%
Computer Aided Diagnosis
8%
Dimensionality
8%
High Resolution
8%
Centerline
8%
One Dimensional
8%
Medical Image Segmentation
8%
Hyperspectral Image
8%
Hyperspectral Data
8%
Deformable Model
8%
Intensive Care Unit
8%
Lymphocyte
8%
Two Dimensional
8%
Iso
8%
Kinematic Model
8%
Microalgae
8%
Noisy Image
8%
Network Edge
8%
Regularization
8%
Field Programmable Gate Arrays
8%
Signal Output
8%
Congruency
8%
Fibre Segment
8%
