PMID- 34797769
OWN - NLM
STAT- MEDLINE
DCOM- 20220418
LR  - 20220528
IS  - 2168-2208 (Electronic)
IS  - 2168-2194 (Linking)
VI  - 26
IP  - 4
DP  - 2022 Apr
TI  - LamNet: A Lesion Attention Maps-Guided Network for the Prediction of Choroidal 
      Neovascularization Volume in SD-OCT Images.
PG  - 1660-1671
LID - 10.1109/JBHI.2021.3129462 [doi]
AB  - Choroidal neovascularization (CNV) volume prediction has an important clinical 
      significance to predict the therapeutic effect and schedule the follow-up. In 
      this paper, we propose a Lesion Attention Maps-Guided Network (LamNet) to 
      automatically predict the CNV volume of next follow-up visit after therapy based 
      on 3-dimentional spectral-domain optical coherence tomography (SD-OCT) images. In 
      particular, the backbone of LamNet is a 3D convolutional neural network (3D-CNN). 
      In order to guide the network to focus on the local CNV lesion regions, we use 
      CNV attention maps generated by an attention map generator to produce the 
      multi-scale local context features. Then, the multi-scale of both local and 
      global feature maps are fused to achieve the high-precision CNV volume 
      prediction. In addition, we also design a synergistic multi-task predictor, in 
      which a trend-consistent loss ensures that the change trend of the predicted CNV 
      volume is consistent with the real change trend of the CNV volume. The 
      experiments include a total of 541 SD-OCT cubes from 68 patients with two types 
      of CNV captured by two different SD-OCT devices. The results demonstrate that 
      LamNet can provide the reliable and accurate CNV volume prediction, which would 
      further assist the clinical diagnosis and design the treatment options.
FAU - Zhang, Yuhan
AU  - Zhang Y
FAU - Ma, Xiao
AU  - Ma X
FAU - Li, Mingchao
AU  - Li M
FAU - Ji, Zexuan
AU  - Ji Z
FAU - Yuan, Songtao
AU  - Yuan S
FAU - Chen, Qiang
AU  - Chen Q
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20220414
PL  - United States
TA  - IEEE J Biomed Health Inform
JT  - IEEE journal of biomedical and health informatics
JID - 101604520
SB  - IM
MH  - Attention
MH  - Choroid
MH  - *Choroidal Neovascularization/diagnostic imaging
MH  - Fluorescein Angiography
MH  - Humans
MH  - Tomography, Optical Coherence/methods
EDAT- 2021/11/20 06:00
MHDA- 2022/04/19 06:00
CRDT- 2021/11/19 17:14
PHST- 2021/11/20 06:00 [pubmed]
PHST- 2022/04/19 06:00 [medline]
PHST- 2021/11/19 17:14 [entrez]
AID - 10.1109/JBHI.2021.3129462 [doi]
PST - ppublish
SO  - IEEE J Biomed Health Inform. 2022 Apr;26(4):1660-1671. doi: 
      10.1109/JBHI.2021.3129462. Epub 2022 Apr 14.