Feb 2015 - Feb 2020, Medical physics, Ph.D. (integrated program)

Sungkyunkwan University, Republic of Korea

Dept. Samsung Advanced Institute for Health Sciences & Technology (SAIHST)

Medical Physics Lab. (Major advisor: Prof. Youngyih Han, [email protected])

Mar 2012 - Aug 2014, Computer Engineering 

Yonsei University, Republic of Korea

Dept. Computer Engineering and Communication and Information Engineering.

Bachelor's degree (Major advisor: Prof. Jaekwon Kim)

Mar 2008 - Aug 2014, Radiological science

Mar 2020- Present, National cancer center, Republic of Korea

Feb 2014 - Feb 2015, Samsung Medical Center, Republic of Korea

Jun 2013 - Aug 2013, National Cancer Center, Republic of Korea

Summer internship, Dept. Medical engineering

- Lymphedema measurement using KINECT volume reconstruction method [link]

Jan 2013 - Feb 2013, Vatech Vision Research Center, Republic of Korea

2021, Asia-oceania Federation of Organization Medical physics Best Ph.D Award 
Winnner: [link]

2021, Body morphometry AI segmetation challenge (보건복지부)
Top prize:
Kidney and kidney tumor segmetation network by using nnUnet and STAPLE algorithm

2021, 9th Japan-Korea Joint meeting on Medical physics (한-일 의학물리학회) 
Young Investigation Award:
Beam Angle Optimization for Double-Scattering Proton Delivery Technique Using an Eclipse Application Programming Interface and Convolutional Neural Network

2021, 9th Japan-Korea Joint meeting on Medical physics (한-일 의학물리학회) 
Young Investigation Award:
Beam Angle Optimization for Double-Scattering Proton Delivery Technique Using an Eclipse Application Programming Interface and Convolutional Neural Network

2020, Korean Society of Medical Physics (한국의학물리학회)

Excellent Review Paper Award:

Review paper: Deep-learning in Radiation Oncology [link]

2019, 57th Korean Society of Medical Physics (한국의학물리학회)

Oral presentation Award:

3D isocenters quality assurance in radiation treatment room using a motion capture camera system [link]

2018, 16th Korean Society of Medical Physics for Radiosurgery (방사선수술물리연구회)

Oral presentation Award:

Two-dimensional time-resolved mirrorless scintillation detector for pretreatment QA [link]

2018, 56th Korean Society of Medical Physics (한국의학물리학회)

Oral presentation Award:

Prediction of the patient respiratory signal using deep learning model: LSTM [link] 

2017, 8th Japan-Korea Joint meeting on Medical physics (한-일 의학물리학회)

Young Investigation Award:

Development of a mirrorless compact scintillation detector 

2017, 15th Korean Society of Medical Physics for Radiosurgery (방사선수술물리연구회)

2017, AMC-Microsoft Medical Big data Analysis Contest 

(아산-마이크로소프트 공동주관 의료 빅데이터 분석 콘테스트)

2013, Capstone competition held by Yonsei Univ. (연세대학교 Capstone 경진대회)

3rd prize:
Development of Gamma camera simulator using Arduino [link]

2013, Research poster competition held by the National Cancer Center

(국립암센터 학생연구원 포스터 발표대회)

2012, Field practice contest held by Yonsei Univ. 

(연세대학교 겨울학기 현장실습 경진대회)

2012, Presentation competition held by Korea Nuclear Energy Agency

(한국원자력문화재단 NERSTAR 전국 PT경진대회)

Wonjoong Cheon, Sang Hee Ahn, Seonghoon Jeong, Se Byeong Lee, Dongho Shin, Young Kyung Lim, Jong Hwi Jeong, Sang Hee Youn, Sung Uk Lee, Sung Ho Moon, Tae Hyun Kim and Haksoo Kim*, “Beam Angle Optimization for Double-Scattering Proton Delivery Technique Using an Eclipse Application Programming Interface and Convolutional Neural Network”, Frontier Oncology (Published)

Wonjoong Cheon, Hyunuk Jung, Moonhee Lee, Jinhyeop Lee, Sung Jin Kim, Sungkoo Cho, Youngyih Han*, “Development of a time-resolved mirrorless scintillation detector”, PlusOne, Vol. 16 no 2, e0246742, 2021 (Published)

Moonhee Lee, Sunghwan Ahn, Wonjoong Cheon, Youghyih Han*, “Linear Energy Transfer Dependence Correction of Spread-Out Bragg Peak Measured by EBT3 Film for Dynamically Scanned Proton Beams”, Progress in Medical Physics, Vol. 31, no. 4, pp. 135-144, 2020 (Published)

Wonjoong Cheon, Haksoo Kim*, Jinsung Kim*, “Review paper: Deep Learning in Radiation Oncology”, Progress in Medical Physics, Vol. 31, no. 3, pp. 111-123, 2020 (Published) 

Han Gyul Yoon, Wonjoong Cheon, Sang Woon Jeong, Hye Seung Kim, Kyunga Kim, Heerim Nam, Youngyih Han*, and Do Hoon Lim*, “Multi-Parametric Deep Learning Model for Prediction of Overall Survival after Postoperative Concurrent Chemoradiotherapy in Glioblastoma Patients”, Cancers Vol. 12, no. 8, pp. 2284-2296, 2020 (Published, Co-first author)

Wonjoong Cheon, Kwanghyun Jo, Sung Hwan Ahn, Junsang Cho, Youngyih Han*, “Quality assurance of isocenters for passive proton beam nozzles using motion capture cameras”, Physica Medica Vol. 70, pp. 139-144, 2020 (Published) 

Wonjoong Cheon, Byung Jun Min*, Young-Seok Seo, Ho Lee, “Non-blind deconvolution with an alternating direction method of multipliers (ADMM) after noise reduction in nondestructive testing”, Journal of Instrument, Vol. 14, no. 11, pp. P11032, 2019 (Published)

Wonjoong Cheon, Sung Jin Kim, Kyuseok Kim, Moonhee Lee, Jinhyeop Lee, Kwanghyun Jo, Sungkoo Cho, Hyosung Cho, Youngyih Han*, “Feasibility of two-dimensional dose distribution deconvolution using convolution neural networks”, Medical Physics, Vol. 46, no. 12, pp. 5833-5847 (Published)

Wonjoong Cheon, Sung Jin Kim, Ui-jung Hwang, Byung Jun Min*, Youngyih Han*, “Feasibility study of the fluence-to-dose network (FDNet) for patient-specific IMRT quality assurance”, Journal of Korean Physics Society. Vol. 75, no. 9, pp. 724-734, 2019 (Published) 

Wonjoong Cheon, Junhyeop Lee, Byung Jun Min*, Youngyih Han*, “Super-Resolution Model for High-Precision In Vivo Proton Range Using a Stereo Gamma Camera: A Feasibility Study”, Journal of Korean Physics Society, Vol. 75, no. 8, pp. 617-627, 2019 (Published) 

Wonjoong Cheon, Junsang Cho, Sung Hwan Ahn, Youngyih Han*, and Doo Ho Choi. “High precision quality assurance using motion capture cameras for six-degrees of freedom robotic couches.”, Physica Medica Vol. 49, pp. 28-33, 2018 (Published)

Sang Hee Ahn, Kwangzoo Chung, Jung Wook Shin, Wonjoong Cheon, Youngyih Han*, Hee Chul Park, and Doo Ho Choi. “Study on dependence of dose enhancement on cluster morphology of gold nanoparticles in radiation therapy using a body-centred cubic model.”, Physics in Medicine & Biology, Vol. 62, no. 19, pp. 7729-7740, 2017 (Published)

Junsang Cho, Wonjoong Cheon, Sang Hee Ahn, Hyunuk Jung, Heesoon Sheen, Hee Chul Park, and Youngyih Han*. “Development of a real-time internal and external marker tracking system for particle therapy: a phantom study using patient tumor trajectory data.” Journal of radiation research, Vol. 58, no. 5, pp. 710-719, 2017 (Published)

Junsang Cho, Wonjoong Cheon, Sang Hee Ahn, Moonhee Lee, Hee Chul Park, and Youngyih Han*. “Development of a Real-Time Internal and External Marker Based Gating System for Proton Therapy.” Progress in Medical Physics, Vol. 28, no. 3, pp. 92-99, 2017 (Published)

Radiation dose measurement device and measurement method
Status: Filed (Filed: Jun. 22, 2021) | Country: United Statue America  Application | No.: US 11,041,963 B2 |
Role: Inventor 

System and method for evaluating motion of radiation diagnosis and therapy apparatus
Status: Patented (Issued: Feb. 26, 2021) | Country: Republic of Korea Application | No.: 10-2223769 |
Role: Inventor 

System and method for quality assurance of radiation isocenter of radiation diagnosis and therapy device

System and method for quality assurance of three-dimensional isocenter of radiation diagnosis and treatment device

Motion evaluation system and method

System for motion evaluation and Method using the same 

Evaluation system of radiation therapy 

Apparatus and method for measuring radiation dose

Dynalog file analyzer for pretreatment quality assurance (C-2018-039489, Dec. 24, 2018)

치료전 품질보증을 위한 다이나로그 파일 (Dynalog file) 분석기

Database generation program for deep learning based radiation error prediction model
(C-2017-034430, Dec. 18, 2017)

방사선 오류예측 딥러닝 모델을 위한 데이터베이스 생성 프로그램

Extraction and conversion program of radiation therapy information for Monte Carlo dose calculation (C-2017-003520, Feb. 8, 2017)

몬테칼로 선량계산을 위한 방사선치료 정보 추출 및 변환 프로그램

Absorbed dose analysis program using scintillation detector (C-2016-008355, Mar. 14, 2016) 

섬광검출기를 이용한 흡수선량 분석프로그램 (C-2016-008355 호, 2016년 3월 14일)

New quality assurance method using motion tracker for 6D robotic couch (C-2015-013823, May 16, 2015)

Organ segmentation: Liver

The project of liver segmentation has been studied and presented at SNU-TF (Seoul university-Tensorflow Korea).

The LiTs Competition data was used for training network. Backbone architecture is "U-net" [link]

Respiratory signal prediction

The project of patient respiratory signal prediction using Long Short Term Memory (LSTM) was studied and presented at Korea society of medical physics (KSMP), Spring, 2018.

The respiratory signal was acquired from 4D CT data. Backbone architecture is LSTM.

In this study, LSTM method was compared with Multi-later perceptron and Decision Tree. [link]

Status: Under description for research paper

Multi-organ segmentation

The project of "Deep learning application to patient-specific organs at risk auto-segmentation" was studied and presented at KOSRO (Korea society for radiation oncology), Fall, 2018.

Reduced field or cone down field techniques utilizing multiple CT scans are commonly used for adaptive radiation therapy (ART) in radiation oncology. In this process, not only the target but also the organs at risk (OAR) need to be manually delineated at each CT scans. In this study, a deep learning method is investigated to automatically segment the OARs in the cone down CTs without Bigdata [link]

Status: Under description for research paper

Two-dimensional dose distribution deconvolution using convolutional netural network

Accurate dose measurement of the penumbra region is essential to measure the dose distribution most closer to the true dose distribution using a scintillation detector. However, the in-house developed scintillation detector has shorter penumbra width. Therefore, the accumulated dose distribution measured by the scintillation detector contains errors.
The objective of this study is to recover true dose distribution from the measured dose distribution using a convolution neural network named PenumbraNet.

Status: Medical Physics (major revision)

Stereo-gamma camera with super-resolution model for in vivo proton range verification

In this project, deep-learning based super-resolution technique was applied to stereo portable gamma camera (SPGC) system.
The SPGC system could track the position of radiation source as 3D coordiates (x,y,z). 

The developed super-resolution technique improved the tracking accuracy of SPGC system for in vivo proton range verification 

Status: Journal of Korea Physics of Society (minor-revision)

Feasibility study of fluence to dose network (FDNet) for patient-specific IMRT quality assurance

In this project, we proposed a new method to perform pQA by predicting the delivered dose distribution in the water phantom using actual machine parameters of Dynalog file for all timesteps through the fluence to dose network (FDNet). 

Status: Journal of Korea Physics of Society (submission)

LINAC modeling (Geant4)

 The project of LINAC (NovlisTx 6MV) was carried out by H.Jung.

 I supported this project for 

•  Multi-threading process [code-1], [code-2]
  
•  Extracting MLC positions from RT-Plan file to Geant4  [code]
  
•  Importing CT data to Geant4 for 3D dose calculation [code]
  

Proton nozzle modeling (Geant4)

 The project of Proton nozzle modeling was carried out by J.Lee.

  I supported this project for 

•  Conversion from the position log file to the intensity of Tesla [link]
  
•  Multileaf Collimator (MLC) for proton nozzle designed CAD (*.stl, *.ply) [link]
  

CBCT modeling (GATE)

 The project of Cone-beam CT was carried out by W.Cheon 

•  Calculate projection images [link]
  
•  Calculated CT-Dose Index (CTDI) [link]

Dual-Gamma camera modeling (Geant4)

 The project of Dual-gamma camera was modeled for 
"Feasibility study of 3-D isotope position tracking system using portable  gamma cameras"  [link] [code]

Scintillator modeling (Geant4)

 The PI-200 (Mitsubishi chemical, Japan) was modeled in Geant4  [code-1] [code-2]

Time-resolved mirrorless scintillation detector (TRMLSD)

High precision quality assurance for six-degrees of freedom robotic couches

Automatic 6-D robotic couch QA was performed using Visual Tracking System (VTS).

The VTS was consist of four Bonita B10 infra-red camera, which could tracking Infra-reflective (IR) markers as 3D coordinates. 

For measuring IR marker in treatment room coordinate system, coordinate matching algorithm was applied between treatment room coordinate system and VTS coordinate system. [link] [paper]

Three-dimensional quality assurance of isocenters coincidence for passively scattered proton beam delivery system using motion capture cameras

3D isocenter coincidence QA was performed using VTS and in-house phantom named Eagle. 

The isocenters which exist in radiation treatment room should be a single point, but it is hard to defined as a single point. 

The aim of this study is to define the 3D position of each isocenter as 3D Cartesian coordinates. [link]

Status: Physica Medica (submission)