Evidence map›Paper›PMID 35965563›Full record

ArticleFrontiers in oncology2022

Structure boundary-preserving U-Net for prostate ultrasound image segmentation.

Hui Bi, Jiawei Sun, Yibo Jiang, Xinye Ni, Huazhong Shu

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.6field-weighted citation impact, top 33% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 6 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 1 country.

Hui BiDepartment of Radiation Oncology, The Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou, China.
Jiawei SunJiangsu Province Engineering Research Center of Medical Physics, Changzhou, China.
Yibo JiangSchool of Electrical and Information Engineering, Changzhou Institute of Technology, Changzhou, China.
Xinye NiDepartment of Radiation Oncology, The Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou, China.
Huazhong ShuLaboratory of Image Science and Technology, Southeast University, Nanjing, China.
Southeast University · CNChangzhou Institute of Technology · CNNanjing Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prostate cancer diagnosis is performed under ultrasound-guided puncture for pathological cell extraction. However, determining accurate prostate location remains a challenge from two aspects: (1) prostate boundary in ultrasound images is always ambiguous; (2) the delineation of radiologists always occupies multiple pixels, leading to many disturbing points around the actual contour. We proposed a boundary structure-preserving U-Net (BSP U-Net) in this paper to achieve precise prostate contour. BSP U-Net incorporates prostate shape prior to traditional U-Net. The prior shape is built by the key point selection module, which is an active shape model-based method. Then, the module plugs into the traditional U-Net structure network to achieve prostate segmentation. The experiments were conducted on two datasets:

Indexed as

ASM-based key points selectiondeep learningprostate ultrasound image segmentationshape priorU-Net architecture

Identifiers

PMID35965563
PMCPMC9366193
OpenAlexW4288077304

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.