TY - JOUR
T1 - RETOUCH
T2 - The Retinal OCT Fluid Detection and Segmentation Benchmark and Challenge
AU - Bogunovic, Hrvoje
AU - Venhuizen, Freerk
AU - Klimscha, Sophie
AU - Apostolopoulos, Stefanos
AU - Bab-Hadiashar, Alireza
AU - Bagci, Ulas
AU - Beg, Mirza Faisal
AU - Bekalo, Loza
AU - Chen, Qiang
AU - Ciller, Carlos
AU - Gopinath, Karthik
AU - Gostar, Amirali K.
AU - Jeon, Kiwan
AU - Ji, Zexuan
AU - Kang, Sung Ho
AU - Koozekanani, Dara D.
AU - Lu, Donghuan
AU - Morley, Dustin
AU - Parhi, Keshab K.
AU - Park, Hyoung Suk
AU - Rashno, Abdolreza
AU - Sarunic, Marinko
AU - Shaikh, Saad
AU - Sivaswamy, Jayanthi
AU - Tennakoon, Ruwan
AU - Yadav, Shivin
AU - De Zanet, Sandro
AU - Waldstein, Sebastian M.
AU - Gerendas, Bianca S.
AU - Klaver, Caroline
AU - Sanchez, Clara I.
AU - Schmidt-Erfurth, Ursula
N1 - Publisher Copyright:
© 1982-2012 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - Retinal swelling due to the accumulation of fluid is associated with the most vision-threatening retinal diseases. Optical coherence tomography (OCT) is the current standard of care in assessing the presence and quantity of retinal fluid and image-guided treatment management. Deep learning methods have made their impact across medical imaging, and many retinal OCT analysis methods have been proposed. However, it is currently not clear how successful they are in interpreting the retinal fluid on OCT, which is due to the lack of standardized benchmarks. To address this, we organized a challenge RETOUCH in conjunction with MICCAI 2017, with eight teams participating. The challenge consisted of two tasks: fluid detection and fluid segmentation. It featured for the first time: all three retinal fluid types, with annotated images provided by two clinical centers, which were acquired with the three most common OCT device vendors from patients with two different retinal diseases. The analysis revealed that in the detection task, the performance on the automated fluid detection was within the inter-grader variability. However, in the segmentation task, fusing the automated methods produced segmentations that were superior to all individual methods, indicating the need for further improvements in the segmentation performance.
AB - Retinal swelling due to the accumulation of fluid is associated with the most vision-threatening retinal diseases. Optical coherence tomography (OCT) is the current standard of care in assessing the presence and quantity of retinal fluid and image-guided treatment management. Deep learning methods have made their impact across medical imaging, and many retinal OCT analysis methods have been proposed. However, it is currently not clear how successful they are in interpreting the retinal fluid on OCT, which is due to the lack of standardized benchmarks. To address this, we organized a challenge RETOUCH in conjunction with MICCAI 2017, with eight teams participating. The challenge consisted of two tasks: fluid detection and fluid segmentation. It featured for the first time: all three retinal fluid types, with annotated images provided by two clinical centers, which were acquired with the three most common OCT device vendors from patients with two different retinal diseases. The analysis revealed that in the detection task, the performance on the automated fluid detection was within the inter-grader variability. However, in the segmentation task, fusing the automated methods produced segmentations that were superior to all individual methods, indicating the need for further improvements in the segmentation performance.
KW - Evaluation
KW - image classification
KW - image segmentation
KW - optical coherence tomography
KW - retina
UR - http://www.scopus.com/inward/record.url?scp=85070239796&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85070239796&partnerID=8YFLogxK
U2 - 10.1109/TMI.2019.2901398
DO - 10.1109/TMI.2019.2901398
M3 - Article
C2 - 30835214
AN - SCOPUS:85070239796
SN - 0278-0062
VL - 38
SP - 1858
EP - 1874
JO - IEEE Transactions on Medical Imaging
JF - IEEE Transactions on Medical Imaging
IS - 8
M1 - 8653407
ER -