| Publication |
Sentence |
Publish Date |
Extraction Date |
Species |
| George Oliveira Barros, Jose Nathan Andrade Muller da Silva, Henrique Machado de Sousa Proenca, Stanley Almeida Araujo, David Campos Wanderley, Luciano Reboucas de Oliveira, Washington Luis Conrado Dos-Santos, Angelo Amancio Duarte, Flavio de Barros Vida. Enhancing Podocyte Degenerative Changes Identification With Pathologist Collaboration: Implications for Improved Diagnosis in Kidney Diseases. IEEE journal of translational engineering in health and medicine. vol 12. 2024-10-29. PMID:39468995. |
the study involved building a new dataset of renal glomeruli images, some with and others without podocyte degenerative changes, and developing a convolutional neural network (cnn) based classifier. |
2024-10-29 |
2024-10-31 |
Not clear |
| Chia-Feng Juang, Ya-Wen Chuang, Guan-Wen Lin, I-Fang Chung, Ying-Chih L. Deep learning-based glomerulus detection and classification with generative morphology augmentation in renal pathology images. Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society. vol 115. 2024-04-10. PMID:38599040. |
this paper proposes a deep convolutional neural network (cnn)-based approach to automatically detect and classify glomeruli with different stains in renal pathology images. |
2024-04-10 |
2024-04-13 |
Not clear |
| Meyke Hermsen, Francesco Ciompi, Adeyemi Adefidipe, Aleksandar Denic, Amélie Dendooven, Byron H Smith, Dominique van Midden, Jan Hinrich Bräsen, Jesper Kers, Mark D Stegall, Péter Bándi, Tri Nguyen, Zaneta Swiderska-Chadaj, Bart Smeets, Luuk B Hilbrands, Jeroen A W M van der Laa. CONVOLUTIONAL NEURAL NETWORKS FOR THE EVALUATION OF CHRONIC AND INFLAMMATORY LESIONS IN KIDNEY TRANSPLANT BIOPSIES. The American journal of pathology. 2022-07-17. PMID:35843265. |
the cnn results were used to quantify healthy and sclerotic glomeruli, interstitial fibrosis, tubular atrophy, and inflammation both within non-atrophic and atrophic tubuli, and in areas of interstitial fibrosis. |
2022-07-17 |
2023-08-14 |
Not clear |
| Zhaohui Zheng, Xiangsen Zhang, Jin Ding, Dingwen Zhang, Jihong Cui, Xianghui Fu, Junwei Han, Ping Zh. Deep Learning-Based Artificial Intelligence System for Automatic Assessment of Glomerular Pathological Findings in Lupus Nephritis. Diagnostics (Basel, Switzerland). vol 11. issue 11. 2021-11-30. PMID:34829330. |
the cnn models yolov4 and vgg16 were employed to localise the glomeruli and classify glomerular lesions (slight/severe impairments or sclerotic lesions). |
2021-11-30 |
2023-08-13 |
Not clear |
| Gloria Bueno, M Milagro Fernandez-Carrobles, Lucia Gonzalez-Lopez, Oscar Deni. Glomerulosclerosis identification in whole slide images using semantic segmentation. Computer methods and programs in biomedicine. vol 184. 2021-01-06. PMID:31891905. |
in this paper, semantic segmentation based on convolutional neural networks (cnn) is proposed to detect glomeruli using whole slide imaging (wsi) follows by a classification cnn to divide the glomeruli into normal and sclerosed. |
2021-01-06 |
2023-08-13 |
Not clear |
| Michael Gadermayr, Ann-Kathrin Dombrowski, Barbara Mara Klinkhammer, Peter Boor, Dorit Merho. CNN cascades for segmenting sparse objects in gigapixel whole slide images. Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society. vol 71. 2020-04-03. PMID:30472409. |
to tackle the thereby arising challenges, we propose two different cnn cascade approaches which are subsequently applied to segment the glomeruli in whole slide images of the kidney and compared with conventional fully-convolutional networks. |
2020-04-03 |
2023-08-13 |
Not clear |