Results 151 to 160 of about 94,278 (212)

Impact of Imaging Modality on AI-Based Detection of Incidental Maxillary Sinus Pathology: Comparison of Panoramic Radiography and CBCT. [PDF]

Diagnostics (Basel)
Lackowska A, Kazimierczak N, Chwarścianek N, Sultani N, Serafin Z, Kazimierczak W.   +5 more
europepmc   +1 more source

DSCANet: Integrating dual encoder and spatial cross-attention for polyp segmentation. [PDF]

PLoS One
Su J, Shi T, Adamyk B.
europepmc   +1 more source

Multi-Scale Cross-Attention Multiple Instance Learning Network for Automated Classification of Colorectal Polyps. [PDF]

Cancer Inform
Ikezogwo W, Liu Y, Hosny K, Henriksen J, Ricciotti R, Rawlani M, Swanson P, Mathias PC, Hoffman NG, Baird G, Gonzalez-Cuyar LF, Shapiro L, Reddi D.   +12 more
europepmc   +1 more source

Rare Osseous Metaplasia in a Hyperplastic Gastric Polyp. [PDF]

ACG Case Rep J
Conder E, Brenner A, Campbell D, Rueckert J, Brazel E.   +4 more
europepmc   +1 more source

Ultrasound-Guided Endometrial Polypectomy Performed in an Office Setting Without Hysteroscopy. [PDF]

Cureus
Bayyarapu VB, Gundabattula SR, Rangaram P, Ashrafi S.   +3 more
europepmc   +1 more source

A case of gallbladder adenoma causing gallbladder haemorrhage. [PDF]

J Surg Case Rep
Yokoyama T, Sui K, Okawa S, Mukohara F, Iwata K, Tsudaka S, Takahashi Y, Otani H, Tanaka N, Yano M, Ohashi R.   +10 more
europepmc   +1 more source

Simple U-net based synthetic polyp image generation: Polyp to negative and negative to polyp [PDF]

Biomedical Signal Processing and Control, 2022
Synthetic polyp generation is a good alternative to overcome the privacy problem of medical data and the lack of various polyp samples. In this study, we propose a deep learning-based polyp image generation framework that generates synthetic polyp images
Hemin Ali Qadir, Ilangko Balasingham, Younghak Shin   +2 more
exaly   +2 more sources