These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
115 related articles for article (PubMed ID: 38343048)
21. High-resolution deep transferred ASPPU-Net for nuclei segmentation of histopathology images. Chanchal AK; Lal S; Kini J Int J Comput Assist Radiol Surg; 2021 Dec; 16(12):2159-2175. PubMed ID: 34622381 [TBL] [Abstract][Full Text] [Related]
22. NucleiSegNet: Robust deep learning architecture for the nuclei segmentation of liver cancer histopathology images. Lal S; Das D; Alabhya K; Kanfade A; Kumar A; Kini J Comput Biol Med; 2021 Jan; 128():104075. PubMed ID: 33190012 [TBL] [Abstract][Full Text] [Related]
23. ADR-Net: Context extraction network based on M-Net for medical image segmentation. Ji L; Jiang X; Gao Y; Fang Z; Cai Q; Wei Z Med Phys; 2020 Sep; 47(9):4254-4264. PubMed ID: 32602963 [TBL] [Abstract][Full Text] [Related]
24. NAMSTCD: A Novel Augmented Model for Spinal Cord Segmentation and Tumor Classification Using Deep Nets. Mohanty R; Allabun S; Solanki SS; Pani SK; Alqahtani MS; Abbas M; Soufiene BO Diagnostics (Basel); 2023 Apr; 13(8):. PubMed ID: 37189520 [TBL] [Abstract][Full Text] [Related]
25. Nuclei instance segmentation from histopathology images using Bayesian dropout based deep learning. Gudhe NR; Kosma VM; Behravan H; Mannermaa A BMC Med Imaging; 2023 Oct; 23(1):162. PubMed ID: 37858043 [TBL] [Abstract][Full Text] [Related]
26. Large scale tissue histopathology image classification, segmentation, and visualization via deep convolutional activation features. Xu Y; Jia Z; Wang LB; Ai Y; Zhang F; Lai M; Chang EI BMC Bioinformatics; 2017 May; 18(1):281. PubMed ID: 28549410 [TBL] [Abstract][Full Text] [Related]
27. A dense multi-path decoder for tissue segmentation in histopathology images. Vu QD; Kwak JT Comput Methods Programs Biomed; 2019 May; 173():119-129. PubMed ID: 31046986 [TBL] [Abstract][Full Text] [Related]
28. Fully automated lesion segmentation and visualization in automated whole breast ultrasound (ABUS) images. Lee CY; Chang TF; Chou YH; Yang KC Quant Imaging Med Surg; 2020 Mar; 10(3):568-584. PubMed ID: 32269918 [TBL] [Abstract][Full Text] [Related]
29. A Multi-Stage Approach to Breast Cancer Classification Using Histopathology Images. Bagchi A; Pramanik P; Sarkar R Diagnostics (Basel); 2022 Dec; 13(1):. PubMed ID: 36611418 [TBL] [Abstract][Full Text] [Related]
30. Conventional Machine Learning versus Deep Learning for Magnification Dependent Histopathological Breast Cancer Image Classification: A Comparative Study with Visual Explanation. Boumaraf S; Liu X; Wan Y; Zheng Z; Ferkous C; Ma X; Li Z; Bardou D Diagnostics (Basel); 2021 Mar; 11(3):. PubMed ID: 33809611 [TBL] [Abstract][Full Text] [Related]
31. Deep Learning Networks for Breast Lesion Classification in Ultrasound Images: A Comparative Study. Ferreira MR; Torres HR; Oliveira B; de Araujo ARVF; Morais P; Novais P; Vilaca JL Annu Int Conf IEEE Eng Med Biol Soc; 2023 Jul; 2023():1-4. PubMed ID: 38083151 [TBL] [Abstract][Full Text] [Related]
32. Abnormality classification and localization using dual-branch whole-region-based CNN model with histopathological images. Oyelade ON; Ezugwu AE; Venter HS; Mirjalili S; Gandomi AH Comput Biol Med; 2022 Oct; 149():105943. PubMed ID: 35986967 [TBL] [Abstract][Full Text] [Related]
33. DeepHistoNet: A robust deep-learning model for the classification of hepatocellular, lung, and colon carcinoma. Kadirappa R; S D; R P; Ko SB Microsc Res Tech; 2024 Feb; 87(2):229-256. PubMed ID: 37750465 [TBL] [Abstract][Full Text] [Related]
34. Breast cancer histopathological images classification based on deep semantic features and gray level co-occurrence matrix. Hao Y; Zhang L; Qiao S; Bai Y; Cheng R; Xue H; Hou Y; Zhang W; Zhang G PLoS One; 2022; 17(5):e0267955. PubMed ID: 35511877 [TBL] [Abstract][Full Text] [Related]
35. Comparative Study of First Order Optimizers for Image Classification Using Convolutional Neural Networks on Histopathology Images. Kandel I; Castelli M; Popovič A J Imaging; 2020 Sep; 6(9):. PubMed ID: 34460749 [TBL] [Abstract][Full Text] [Related]
36. Automated classification of histopathology images using transfer learning. Talo M Artif Intell Med; 2019 Nov; 101():101743. PubMed ID: 31813483 [TBL] [Abstract][Full Text] [Related]
37. VGGIN-Net: Deep Transfer Network for Imbalanced Breast Cancer Dataset. Saini M; Susan S IEEE/ACM Trans Comput Biol Bioinform; 2023; 20(1):752-762. PubMed ID: 35349449 [TBL] [Abstract][Full Text] [Related]
38. DRDA-Net: Dense residual dual-shuffle attention network for breast cancer classification using histopathological images. Chattopadhyay S; Dey A; Singh PK; Sarkar R Comput Biol Med; 2022 Jun; 145():105437. PubMed ID: 35339096 [TBL] [Abstract][Full Text] [Related]
39. GC-EnC: A Copula based ensemble of CNNs for malignancy identification in breast histopathology and cytology images. Dey S; Mitra S; Chakraborty S; Mondal D; Nasipuri M; Das N Comput Biol Med; 2023 Jan; 152():106329. PubMed ID: 36473342 [TBL] [Abstract][Full Text] [Related]
40. Application of Imaging Examination Based on Deep Learning in the Diagnosis of Viral Senile Pneumonia. Deng X; Ge X; Xue Q; Liu H Contrast Media Mol Imaging; 2022; 2022():6964283. PubMed ID: 35694707 [TBL] [Abstract][Full Text] [Related] [Previous] [Next] [New Search]