CUST: CNN for ultrasound thermal image reconstruction using sparse time-of-flight information

Younsu Kim, Chloé Audigier, Emran M.A. Anas, Jens Ziegle, Michael Friebe, Emad Boctor

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Thermotherapy is a clinical procedure to induce a desired biological tissue response through temperature changes. To precisely operate the procedure, temperature monitoring during the treatment is essential. Ultrasound propagation velocity in biological tissue changes as temperature increases. An external ultrasound element was integrated with a bipolar radiofrequency (RF) ablation probe to collect time-of-flight information carried by ultrasound waves going through the ablated tissues. Recovering temperature at the pixel level from the limited information acquired from this minimal setup is an ill-posed problem. Therefore, we propose a learning approach using a designed convolutional neural network. Training and testing were performed with temperature images generated with a computational bioheat model simulating a RF ablation. The reconstructed thermal images were compared with results from another sound velocity reconstruction method. The proposed method showed better stability and accuracy for different ultrasound element locations. Ex-vivo experiments were also performed on porcine liver to evaluate the proposed temperature reconstruction method.

Original languageEnglish (US)
Title of host publicationSimulation, Image Processing, and Ultrasound Systems for Assisted Diagnosis and Navigation - International Workshops, POCUS 2018, BIVPCS 2018, CuRIOUS 2018, and CPM 2018, Held in Conjunction with MICCAI 2018, Proceedings
EditorsStephen Aylward, Amber Simpson, Lena Maier-Hein, Anne Martel, Matthieu Chabanas, João Manuel Tavares, Ingerid Reinertsen, Zeike Taylor, Yiming Xiao, Keyvan Farahani, Danail Stoyanov, Shuo Li, Hassan Rivaz
PublisherSpringer Verlag
Pages29-37
Number of pages9
ISBN (Print)9783030010447
DOIs
StatePublished - Jan 1 2018
EventInternational Workshop on Point-of-Care Ultrasound, POCUS 2018, the International Workshop on Bio-Imaging and Visualization for Patient-Customized Simulations, BIVPCS 2017, the International Workshop on Correction of Brainshift with Intra-Operative Ultrasound, CuRIOUS 2018, and the International Workshop on Computational Precision Medicine, CPM 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018 - Granada, Spain
Duration: Sep 16 2018Sep 20 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11042 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherInternational Workshop on Point-of-Care Ultrasound, POCUS 2018, the International Workshop on Bio-Imaging and Visualization for Patient-Customized Simulations, BIVPCS 2017, the International Workshop on Correction of Brainshift with Intra-Operative Ultrasound, CuRIOUS 2018, and the International Workshop on Computational Precision Medicine, CPM 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018
CountrySpain
CityGranada
Period9/16/189/20/18

Fingerprint

Time-of-flight
Image Reconstruction
Ultrasound
Image reconstruction
Ultrasonics
Biological Tissue
Ablation
Tissue
Temperature
Acoustic wave velocity
Ill-posed Problem
Liver
Computational Model
Hot Temperature
Probe
Pixel
Pixels
Monitoring
Neural Networks
Propagation

Keywords

  • Bipolar ablation
  • CNN
  • Hyperthermia
  • Temperature image reconstruction
  • Thermotherapy
  • Ultrasound
  • Ultrasound thermal monitoring

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Kim, Y., Audigier, C., Anas, E. M. A., Ziegle, J., Friebe, M., & Boctor, E. (2018). CUST: CNN for ultrasound thermal image reconstruction using sparse time-of-flight information. In S. Aylward, A. Simpson, L. Maier-Hein, A. Martel, M. Chabanas, J. M. Tavares, I. Reinertsen, Z. Taylor, Y. Xiao, K. Farahani, D. Stoyanov, S. Li, ... H. Rivaz (Eds.), Simulation, Image Processing, and Ultrasound Systems for Assisted Diagnosis and Navigation - International Workshops, POCUS 2018, BIVPCS 2018, CuRIOUS 2018, and CPM 2018, Held in Conjunction with MICCAI 2018, Proceedings (pp. 29-37). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11042 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-01045-4_4

CUST : CNN for ultrasound thermal image reconstruction using sparse time-of-flight information. / Kim, Younsu; Audigier, Chloé; Anas, Emran M.A.; Ziegle, Jens; Friebe, Michael; Boctor, Emad.

Simulation, Image Processing, and Ultrasound Systems for Assisted Diagnosis and Navigation - International Workshops, POCUS 2018, BIVPCS 2018, CuRIOUS 2018, and CPM 2018, Held in Conjunction with MICCAI 2018, Proceedings. ed. / Stephen Aylward; Amber Simpson; Lena Maier-Hein; Anne Martel; Matthieu Chabanas; João Manuel Tavares; Ingerid Reinertsen; Zeike Taylor; Yiming Xiao; Keyvan Farahani; Danail Stoyanov; Shuo Li; Hassan Rivaz. Springer Verlag, 2018. p. 29-37 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11042 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kim, Y, Audigier, C, Anas, EMA, Ziegle, J, Friebe, M & Boctor, E 2018, CUST: CNN for ultrasound thermal image reconstruction using sparse time-of-flight information. in S Aylward, A Simpson, L Maier-Hein, A Martel, M Chabanas, JM Tavares, I Reinertsen, Z Taylor, Y Xiao, K Farahani, D Stoyanov, S Li & H Rivaz (eds), Simulation, Image Processing, and Ultrasound Systems for Assisted Diagnosis and Navigation - International Workshops, POCUS 2018, BIVPCS 2018, CuRIOUS 2018, and CPM 2018, Held in Conjunction with MICCAI 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11042 LNCS, Springer Verlag, pp. 29-37, International Workshop on Point-of-Care Ultrasound, POCUS 2018, the International Workshop on Bio-Imaging and Visualization for Patient-Customized Simulations, BIVPCS 2017, the International Workshop on Correction of Brainshift with Intra-Operative Ultrasound, CuRIOUS 2018, and the International Workshop on Computational Precision Medicine, CPM 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, Granada, Spain, 9/16/18. https://doi.org/10.1007/978-3-030-01045-4_4
Kim Y, Audigier C, Anas EMA, Ziegle J, Friebe M, Boctor E. CUST: CNN for ultrasound thermal image reconstruction using sparse time-of-flight information. In Aylward S, Simpson A, Maier-Hein L, Martel A, Chabanas M, Tavares JM, Reinertsen I, Taylor Z, Xiao Y, Farahani K, Stoyanov D, Li S, Rivaz H, editors, Simulation, Image Processing, and Ultrasound Systems for Assisted Diagnosis and Navigation - International Workshops, POCUS 2018, BIVPCS 2018, CuRIOUS 2018, and CPM 2018, Held in Conjunction with MICCAI 2018, Proceedings. Springer Verlag. 2018. p. 29-37. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-01045-4_4
Kim, Younsu ; Audigier, Chloé ; Anas, Emran M.A. ; Ziegle, Jens ; Friebe, Michael ; Boctor, Emad. / CUST : CNN for ultrasound thermal image reconstruction using sparse time-of-flight information. Simulation, Image Processing, and Ultrasound Systems for Assisted Diagnosis and Navigation - International Workshops, POCUS 2018, BIVPCS 2018, CuRIOUS 2018, and CPM 2018, Held in Conjunction with MICCAI 2018, Proceedings. editor / Stephen Aylward ; Amber Simpson ; Lena Maier-Hein ; Anne Martel ; Matthieu Chabanas ; João Manuel Tavares ; Ingerid Reinertsen ; Zeike Taylor ; Yiming Xiao ; Keyvan Farahani ; Danail Stoyanov ; Shuo Li ; Hassan Rivaz. Springer Verlag, 2018. pp. 29-37 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{df05da30fb144cb8a5fd1198a4800aa1,
title = "CUST: CNN for ultrasound thermal image reconstruction using sparse time-of-flight information",
abstract = "Thermotherapy is a clinical procedure to induce a desired biological tissue response through temperature changes. To precisely operate the procedure, temperature monitoring during the treatment is essential. Ultrasound propagation velocity in biological tissue changes as temperature increases. An external ultrasound element was integrated with a bipolar radiofrequency (RF) ablation probe to collect time-of-flight information carried by ultrasound waves going through the ablated tissues. Recovering temperature at the pixel level from the limited information acquired from this minimal setup is an ill-posed problem. Therefore, we propose a learning approach using a designed convolutional neural network. Training and testing were performed with temperature images generated with a computational bioheat model simulating a RF ablation. The reconstructed thermal images were compared with results from another sound velocity reconstruction method. The proposed method showed better stability and accuracy for different ultrasound element locations. Ex-vivo experiments were also performed on porcine liver to evaluate the proposed temperature reconstruction method.",
keywords = "Bipolar ablation, CNN, Hyperthermia, Temperature image reconstruction, Thermotherapy, Ultrasound, Ultrasound thermal monitoring",
author = "Younsu Kim and Chlo{\'e} Audigier and Anas, {Emran M.A.} and Jens Ziegle and Michael Friebe and Emad Boctor",
year = "2018",
month = "1",
day = "1",
doi = "10.1007/978-3-030-01045-4_4",
language = "English (US)",
isbn = "9783030010447",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "29--37",
editor = "Stephen Aylward and Amber Simpson and Lena Maier-Hein and Anne Martel and Matthieu Chabanas and Tavares, {Jo{\~a}o Manuel} and Ingerid Reinertsen and Zeike Taylor and Yiming Xiao and Keyvan Farahani and Danail Stoyanov and Shuo Li and Hassan Rivaz",
booktitle = "Simulation, Image Processing, and Ultrasound Systems for Assisted Diagnosis and Navigation - International Workshops, POCUS 2018, BIVPCS 2018, CuRIOUS 2018, and CPM 2018, Held in Conjunction with MICCAI 2018, Proceedings",

}

TY - GEN

T1 - CUST

T2 - CNN for ultrasound thermal image reconstruction using sparse time-of-flight information

AU - Kim, Younsu

AU - Audigier, Chloé

AU - Anas, Emran M.A.

AU - Ziegle, Jens

AU - Friebe, Michael

AU - Boctor, Emad

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Thermotherapy is a clinical procedure to induce a desired biological tissue response through temperature changes. To precisely operate the procedure, temperature monitoring during the treatment is essential. Ultrasound propagation velocity in biological tissue changes as temperature increases. An external ultrasound element was integrated with a bipolar radiofrequency (RF) ablation probe to collect time-of-flight information carried by ultrasound waves going through the ablated tissues. Recovering temperature at the pixel level from the limited information acquired from this minimal setup is an ill-posed problem. Therefore, we propose a learning approach using a designed convolutional neural network. Training and testing were performed with temperature images generated with a computational bioheat model simulating a RF ablation. The reconstructed thermal images were compared with results from another sound velocity reconstruction method. The proposed method showed better stability and accuracy for different ultrasound element locations. Ex-vivo experiments were also performed on porcine liver to evaluate the proposed temperature reconstruction method.

AB - Thermotherapy is a clinical procedure to induce a desired biological tissue response through temperature changes. To precisely operate the procedure, temperature monitoring during the treatment is essential. Ultrasound propagation velocity in biological tissue changes as temperature increases. An external ultrasound element was integrated with a bipolar radiofrequency (RF) ablation probe to collect time-of-flight information carried by ultrasound waves going through the ablated tissues. Recovering temperature at the pixel level from the limited information acquired from this minimal setup is an ill-posed problem. Therefore, we propose a learning approach using a designed convolutional neural network. Training and testing were performed with temperature images generated with a computational bioheat model simulating a RF ablation. The reconstructed thermal images were compared with results from another sound velocity reconstruction method. The proposed method showed better stability and accuracy for different ultrasound element locations. Ex-vivo experiments were also performed on porcine liver to evaluate the proposed temperature reconstruction method.

KW - Bipolar ablation

KW - CNN

KW - Hyperthermia

KW - Temperature image reconstruction

KW - Thermotherapy

KW - Ultrasound

KW - Ultrasound thermal monitoring

UR - http://www.scopus.com/inward/record.url?scp=85054349781&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85054349781&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-01045-4_4

DO - 10.1007/978-3-030-01045-4_4

M3 - Conference contribution

AN - SCOPUS:85054349781

SN - 9783030010447

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 29

EP - 37

BT - Simulation, Image Processing, and Ultrasound Systems for Assisted Diagnosis and Navigation - International Workshops, POCUS 2018, BIVPCS 2018, CuRIOUS 2018, and CPM 2018, Held in Conjunction with MICCAI 2018, Proceedings

A2 - Aylward, Stephen

A2 - Simpson, Amber

A2 - Maier-Hein, Lena

A2 - Martel, Anne

A2 - Chabanas, Matthieu

A2 - Tavares, João Manuel

A2 - Reinertsen, Ingerid

A2 - Taylor, Zeike

A2 - Xiao, Yiming

A2 - Farahani, Keyvan

A2 - Stoyanov, Danail

A2 - Li, Shuo

A2 - Rivaz, Hassan

PB - Springer Verlag

ER -