Researcher Evidence Record
Chunfeng Lian
This bounded record lists 13 Pith paper rows and 0 imported work rows attributed to this corpus identity. The enumerated, non-disputed paper rows include cs.CV, eess.IV, cs.LG work dated 2020 to 2026. The record describes sources and coverage; it makes no judgment about the person.
Compiled coverage vector
A sourced case file for attributed work. It is neither a profile score nor a verdict about this researcher.
Attributed works
A bounded ledger from the Pith paper and imported-work queries. Counts and source confidence stay with each work.
-
2026 Pith paper
Precision Synthesis of Multi-Tracer PET via VLM-Modulated Rectified Flow for Stratifying Mild Cognitive Impairment
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- paper_authors
- Printed name
- Chunfeng Lian
- Author position
- 7
- Identity state
- provisional
- Review coverage
- Measured: a current Pith review exists.
- Citation counts
- No source count is attached to this work row.
-
2026 Pith paper
Vision-Language Model-Guided Deep Unrolling Enables Personalized, Fast MRI
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- paper_authors
- Printed name
- Chunfeng Lian
- Author position
- 4
- Identity state
- provisional
- Review coverage
- Measured: a current Pith review exists.
- Citation counts
- No source count is attached to this work row.
-
2023 Pith paper
Punctate White Matter Lesion Segmentation in Preterm Infants Powered by Counterfactually Generative Learning
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Chunfeng Lian
- Author position
- 8
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
- No source count is attached to this work row.
-
2023 Pith paper
Forensic Histopathological Recognition via a Context-Aware MIL Network Powered by Self-Supervised Contrastive Learning
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Chunfeng Lian
- Author position
- 8
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
- No source count is attached to this work row.
-
2023 Pith paper
Dual Meta-Learning with Longitudinally Generalized Regularization for One-Shot Brain Tissue Segmentation Across the Human Lifespan
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Chunfeng Lian
- Author position
- 6
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
- No source count is attached to this work row.
-
2023 Pith paper
NeuroExplainer: Fine-Grained Attention Decoding to Uncover Cortical Development Patterns of Preterm Infants
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Chunfeng Lian
- Author position
- 7
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
- No source count is attached to this work row.
-
2022 Pith paper
Two-Stream Graph Convolutional Network for Intra-oral Scanner Image Segmentation
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Chunfeng Lian
- Author position
- 8
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
- No source count is attached to this work row.
-
2021 Pith paper
SkullEngine: A Multi-stage CNN Framework for Collaborative CBCT Image Segmentation and Landmark Detection
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Chunfeng Lian
- Author position
- 3
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
- No source count is attached to this work row.
-
2021 Pith paper
Two-Stage Mesh Deep Learning for Automated Tooth Segmentation and Landmark Localization on 3D Intraoral Scans
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Chunfeng Lian
- Author position
- 2
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
- No source count is attached to this work row.
-
2021 Pith paper
A Self-Supervised Deep Framework for Reference Bony Shape Estimation in Orthognathic Surgical Planning
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Chunfeng Lian
- Author position
- 7
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
- No source count is attached to this work row.
-
2020 Pith paper
TSGCNet: Discriminative Geometric Feature Learning with Two-Stream GraphConvolutional Network for 3D Dental Model Segmentation
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Chunfeng Lian
- Author position
- 7
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
- No source count is attached to this work row.
-
2020 Pith paper
HF-UNet: Learning Hierarchically Inter-Task Relevance in Multi-Task U-Net for Accurate Prostate Segmentation
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Chunfeng Lian
- Author position
- 2
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
- No source count is attached to this work row.
-
2020 Pith paper
MetricUNet: Synergistic Image- and Voxel-Level Learning for Precise CT Prostate Segmentation via Online Sampling
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Chunfeng Lian
- Author position
- 2
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
- No source count is attached to this work row.
Evidence apparatus
The machinery behind this record. Every lane states whether Pith measured it, did not query it, could not reach it, or withheld it.
| Lane | State | Observed | Boundary and source |
|---|---|---|---|
| identity | Measured | 2 | Canonical identity row plus public typed identifiers. source=authors, author_identifiers |
| papers | Measured | 13 of 13 bounded rows | Rows attributed to this author UUID in the Pith corpus. source=paper_authors |
| works | Measured zero | 0 of 0 bounded rows | Imported works not duplicated by the paper ledger. source=author_works |
| reviews | Measured | 2 of 13 bounded rows | Coverage count only. No review outcome is projected onto the person. source=current_verdicts |
| citations | Measured zero | 0 of 13 bounded rows | Counts remain itemized by work and source. source=cited_works |
| coauthors | Measured | 50 of 13 bounded rows | Shared-work edges from admitted paper rows. source=paper_authors |
| account | Unavailable | No public count of 1 bounded rows | Account metadata is separate from corpus evidence. source=users.author_id |
Public identity sources
-
name variant
Chunfeng Lian
Enumerated research scope
- cs.CV7 rows
- eess.IV5 rows
- cs.LG1 rows
- 20203 rows
- 20213 rows
- 20221 rows
- 20234 rows
- 20262 rows
Record scope
The work queries are bounded. Missing rows may mean measured zero, an unavailable source, a query that did not run, or private data that Pith withheld. The lane table keeps those cases separate.
Paper findings remain attached to papers. They do not become findings about this researcher.
Self-published account annex
Linked Pith account
Unavailable No public Pith account is linked to this corpus identity.
The account lane is self-published. Linking proves account control only and changes no corpus fact.