Deep Learning-based Accelerated Analytics for Medical Imaging · This project is funded by State's Key Project of Research and Development Plan in 2017. Saleem Farooqui, Natarajan

Zhao Di

Computer Network Information Center, CAS

GPU Technology Conference 2017, San Jose McEnery Convention Center, May 11, 2017

Deep Learning-based Accelerated

Analytics for Medical Imaging

Medical Image Analysis with Deep Learning

PET

SPECT

the structural information of human tissue anatomy

Metabolic information of human tissue

Pathology Surgery

Robotics

Medical Photography

Medical Image Analysis based on Deep Learning

The characteristics of Medical image:

• dependent on equipment and background highly;

• too much images, differences and it is difficult to integrate;

• image pixels are different: too low or too high;

• individual differences in organisms, and it is easy to deformability;

The advantages of Deep Learning: satisfy large portion of recognition needs of medical

imaging

• this network can achieve the best classification results, such as in image classification

voice recognition;

• make the secondary classification to achieve a higher correct rate;

• the local connection and sharing weight makes it possible to greatly reduce the number of

parameters and enhance the learning ability of complex networks;

• adjust the weight by gradient descent, we can get the global optimal solution or local

optimal solution;

Papers published in the top journals about deep

learning medical imaging (2016.12-2017.3)

• JAMA: Diabetic retinopathy is highly sensitive and highly specific

• Nature: start the skin cancer smartphone screening

• Nature Biomedical Engineering: Diagnosis and monitoring of rare

diseases (cataract)

• Nature Biomedical Engineering: Rapid diagnosis of intraoperative

brain tumors

• Nature Biomedical Engineering: Precise control of neural prostheses

• Nature: Predicting children 's autism is better than traditional methods

Love between Deep Learning and Medical Imaging

Deep Learning Aided Disease Diagnosis

• Brain/Dementia: Cerebrovascular disease, Neuro-degenerative diseases (Alzheimer's disease,

Parkinson's disease, Epilepsy), mental illness (depression, schizophrenia), brain tumors;

• Chest: heart disease, pulmonary nodules / lung cancer, breast nodules/breast cancer;

• Neck: carotid artery test, thyroid cancer;

• Eye: Diabetes eye disease;

• Skin: Skin cancer;

• Abdomen: Liver cancer, Stomach cancer;

• Pelvis: prostate cancer (male), uterine cancer (female)

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Current Status of Social Aging

• The population of the old in Beijing has increazed seriously;

• In 2015 the city's elderly population has more than 3 million;

• By 2030, the elderly resident population in Beijing is expected to exceed 5

million, it is about 30% of the total population;

The Importance of Research

• Senile neurodegenerative disease is one of the "four killers" of the elderly,

including Alzheimer's disease (Alzheimer's disease), Parkinson's disease;

• The incidence of Alzheimer's disease (Alzheimer's disease) in the elderly

population was significantly higher, and over 30%;

• Alzheimer's disease is the highest incidence of senile neurodegenerative

disease (60%);

Deep Learning Aided Alzheimer's Disease Diagnosis

Alzheimer's Disease

阿尔茨海默病（Alzheimer‘s disease）

是一种起病隐匿的进行性发展的神经

系统退行性疾病。阿尔茨海默病导致

脑神经细胞死亡，脑组织缺失。如左

图所示，阿尔茨海默病将导致严重

的脑萎缩临床上以记忆障碍、失语、失用、失认、视空间技能损害、执行功能障碍以及人格和行为改变等全面性痴呆表现为特征，病因迄今未明。

Alzheimer's disease is a chronic neurodegenerative

disease that usually starts slowly and worsens over

time。Alzheimer's disease causes the brain cell

death, brain tissue loss. As shown on the left,

Alzheimer's disease will lead to severe brain

atrophy.

Alzheimer's disease has not yet found an effective

treatment, clinical “Early Detection, Early

Intervention", for the reduction of brain damage in

patients with a very important significance.

Symptoms can include problems with language,

disorientation (including easily getting lost), mood

swings, loss of motivation, not managing self care,

and behavioural issues.

B A

From Blausen.com

The work is funded by the Beijing Natural Science Foundation 2016.


Cognition scales

Hippocampus Volume


在经过30个EPOCH后，分类精确度达到

96.2%，实际测试精度为86.05%。

AD vs MCI vs HC

Improved AlexNet

Tiechui: Deep Learning Aided Alzheimer's Disease Diagnosis

• There is an imaging technique known as “Positron Emission

Tomography,” or PET, that can be a significant aid in diagnosing

Alzheimer’s disease or other common causes of dementia.

• The physician looks for particular patterns of metabolic activity

in the brain which are associated with the most common types of

dementia, including Alzheimer’s disease.

• By proper contrast agent, diagnostic accuracy

using PET scans with clinical findings

approaches 90%, which can be significantly

higher than clinical diagnosis alone.

• Patients can benefit from earlier and possibly more appropriate

treatment that has potential to improve their quality of life as well

as the lives of their loved ones.

• Pre-processing data.

http://radiologyregional.com/radiologyregional/

Improved GoogleNet

Domain Knowledge of Alzheimer's Disease Diagnosis

• Amygdala, hippocampus, inner olfactory cortex structure

marker (linear measurement, volume);

• In the linear index, the width of the temporal width is the

highest;

• The bilateral temporal horn level represents the middle

part of the hippocampus. In this area, a large number of

associated fibers (internal olfactory area, hippocampus,

hippocampus paralysis, etc.) are associated with the brain

and temporal lobe fibers area;

• Linearity is less repetitive and specific;


MRI

PET

CSFOther clinical

diagnosis

fMRI

ROIs

ROIs

ROIs

Mult-channel deep learning model 1



The model of deep learning N

Weighted bayesian network

weightw1

weightw2

weightw3

Weightw(n)

weightw(n-1)

The results of clinical diagnosis

aisle 1

aisle N

……

aisle 1

aisle N

……

aisle 1

aisle N

……

……

……

……

This project is funded by "Beijing Brain Plan" in 2017.











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Deep Learning Aided Parkinson's Disease Diagnosis

• Parkinson's disease (PD) is a long-term degenerative disorder of the central nervous system that mainly affects the motor system. (wiki)

• The motor symptoms of the disease result from the death of cells in the substantia nigra, a region of the midbrain. This results in not

enough dopamine in these areas. (wiki)

• Diagnosis of typical cases is mainly based on symptoms (handwritten dynamics, smartphone data in Kaggle), with tests such as

neuroimaging being used to rule out other diseases. (wiki)

• By MRI, radiologist recognize PD by imaging biomarker.

From Blausen.com

Deep Learning Aided Parkinson's Disease Diagnosis

• Parkinson's disease (PD) is a long-term degenerative

disorder of the central nervous system that mainly affects the

motor system. (wiki)

• The motor symptoms of the disease result from the death of

cells in the substantia nigra, a region of the midbrain. This

results in not enough dopamine in these areas. (wiki)

• Diagnosis of typical cases is mainly based on symptoms

(handwritten dynamics, smartphone data in Kaggle), with

tests such as neuroimaging being used to rule out other

diseases. (wiki)

• By MRI, radiologist recognize PD by imaging biomarker.

• Clinical MRI data (t1, t2, cor-t2): PD, MSA, normal control.

• Stroke;

• Brain tumor;

• HIV Associated Neurocognitive Disorders

(HAND): neurological disorders associated with

HIV infection and AIDS, cognitive impairment is

characterized by mental slowness, trouble with

memory and poor concentration, wiki;

• South Africa continues to be home to the world's

largest population of people living with HIV, wiki;

• Preclinical stage of human immunodeficiency

virus (HIV) associated neurocognitive disorders

(HAND) is the earliest stage performing with no

clinical symptoms but already with

pathophysiological changes.

• By analyzing MRI imaging, deep learning aided

the detection of HAND.

Deep Learning Aided Brain Disease Diagnosis: other Dementia

Beau M. Ances, Tammie L. Benzinger, Jon J. Christensen,et. al., 11C-PiB Imaging of Human Immunodeficiency Virus–Associated Neurocognitive Disorder, JAMA, 2012.










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Deep Learning Aided Liver Disease Diagnosis

► Deep learning aided LI-RADS grading

• Mass-like configuration;

• Arterial-phase hyper-enhancement;

• Portal venous phase hyper-enhancement;

• Increase of ≥1 cm in diameter within 1

year;

• Tumor within the lumen of a vein.

Adapted from Saleem Farooqui, et al.

◄ Deep learning aided Liver Lesions detection:

• automatic liver segmentation and lesion’s

detection.

• extracting imaging features.

• liver lesions classification between benign

and malignant by using the novel deep

learning approaches.

This project is funded by State's Key Project of Research and Development Plan in 2017. Saleem Farooqui, Natarajan Ravendhran, Steven C. Cunningham, Early Hepatocellular Carcinoma: Diagnosing the Difficult Nodule, Journal of Cancer Therapy, 2013, 4, 651-661










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2017/5/19

Computer Network

Information Center

Improved ResNet




• Chest: heart disease, pulmonary nodules / lung cancer, Breast nodules/breast cancer;






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Breast cancer vs breast lesion CaffeNet

https://www.radiopaedia.org/

Deep learning - breast ultrasound image recognition

Finalist (top 5), the Nvidia Tegra K1 CUDA Vision Challenge 2014-2015

CNIC-Nvidia Cooperation

↓ CNIC-Nvidia Joint Lab for Smart Medicine,

The 2016 Big Data Intell igence Forum

(BDA2016) and the first CNIC Artificial

Intelligence Symposium held at the International

Conference Center funded by CAS.

↑ The 2015 Big Data Intelligence Forum

( B D A 2 0 1 5 ) , Opening Ceremony for

CAS/CNIC-Nvidia GPU Research Center.

Thanks！

Documents

Deep Learning-based Accelerated Analytics for Medical Imaging · This project is funded by State's Key Project of Research and Development Plan in 2017. Saleem Farooqui, Natarajan