M‐SSD based on anchor proposal and ResNet101 backbone for placental haemorrhage MRI detection

Abstract MRI (magnetic resonance imaging) images can effectively show the placental haemorrhage area. In view of the special properties and real‐time detection requirements of placental haemorrhage MRI images, this paper has systematically improved the single‐shot multi‐box detector (SSD) target detection algorithm (M‐SSD). First, taking advantage of the particularity of the MRI image, the maximum stable extremum region (MSER) algorithm was used as the anchor proposal network which integrated the proposal information into the feature layer of SSD to avoid the hungry traversal of the original algorithm. Second, after the scale statistics of the placental haemorrhage area in MRI images, the bounding box matching the size of the placental haemorrhage area was redefined, in this way, the scale of the bounding box will have application pertinence, which can effectively improve the detection accuracy of the algorithm. Third, due to the small target property of the placental haemorrhage area in the MRI image, the VGG16 basic network in the original SSD was replaced by ResNet101, this made the algorithm have higher performance in small target detection. Finally, the Placental Haemorrhage MRI Detection Database (PHMD) has been built which is not only a base for this paper, but also for further research in this area.

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Publication Details

Journal
IET Image Processing
Published
2024-08-15
DOI
https://doi.org/10.1049/ipr2.13198
Citations
1
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
0.25

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article

M‐SSD based on anchor proposal and ResNet101 backbone for placental haemorrhage MRI detection

Faming Shao, Tao Zhang, Dong Wang, Heng Zhang et al.
1 citations
IET Image Processing
Brain Tumor Detection and Classification
0.25
article

M‐SSD based on anchor proposal and ResNet101 backbone for placental haemorrhage MRI detection

Faming Shao, Tao Zhang, Dong Wang, Heng Zhang, Juying Dai
article en
1 citations

Abstract

Abstract MRI (magnetic resonance imaging) images can effectively show the placental haemorrhage area. In view of the special properties and real‐time detection requirements of placental haemorrhage MRI images, this paper has systematically improved the single‐shot multi‐box detector (SSD) target detection algorithm (M‐SSD). First, taking advantage of the particularity of the MRI image, the maximum stable extremum region (MSER) algorithm was used as the anchor proposal network which integrated the proposal information into the feature layer of SSD to avoid the hungry traversal of the original algorithm. Second, after the scale statistics of the placental haemorrhage area in MRI images, the bounding box matching the size of the placental haemorrhage area was redefined, in this way, the scale of the bounding box will have application pertinence, which can effectively improve the detection accuracy of the algorithm. Third, due to the small target property of the placental haemorrhage area in the MRI image, the VGG16 basic network in the original SSD was replaced by ResNet101, this made the algorithm have higher performance in small target detection. Finally, the Placental Haemorrhage MRI Detection Database (PHMD) has been built which is not only a base for this paper, but also for further research in this area.

IET Image ProcessingVol. 18(12)
PLA Army Engineering University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 44%
Brain Tumor Detection and Classification
0.25
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