Oesophagus
Multi tool use
Oesophagus (Graece οἰσοφάγος) est hominis et multorum animalium pars apparatus digestorii, per quam alimenta de ore in stomachum meant. Positus inter pharyngem ventriculumque, oesophagus ante columnam vertebralem et pone tracheam situs est. Oesophagus, tuba fibromuscularis comparata, de circiter 25 cm longitudine in hominibus, pone cor et tracheam descendens ducensque usque ad diaphragmam, ubi illam penetrat, postremo in partem superiorem stomachi exinaniens.
Tres sunt oesophagi partes:
- pars cervicalis vel pars colli, usque ad summum thoracem
- pars thoracica, usque ad diaphragma
- pars abdominalis, usque ad cardiam
Sunt etiam tres constrictiones:
- Constrictio pharyngooesophagea
- Constrictio partis thoracicae vel bronchoaortica
- Constrictio phrenica vel diaphragmatica
Morbi oesophagi |
- Atresia oesophagi
- Cancer oesophagi
Diverticula oesophagi
- Dysphagia
- Oesophagus Barrettiensis
- Oesophagitis propter refluctionem
Ruptura oesophagii (in parte syndroma Boerhaave)
Nexus interni
.mw-parser-output .stipula{padding:3px;background:#F7F8FF;border:1px solid grey;margin:auto}.mw-parser-output .stipula td.cell1{background:transparent;color:white}
|
Haec stipula ad medicinam spectat. Amplifica, si potes!
|
|
Cave: notitiae huius paginae nec praescriptiones nec consilia medica sunt.
|
Bibliographia |
- Pagina Encyclopaediae Britannicae de Oesophago
Apparatus digestorius
| Pars superior |
Os • Labia oris et buccae (Cavum oris • Dentes • Glandulae salivariae • Lingua) • Pharynx • Oesophagus • Stomachus • Iecur • ductus choledochus • Vesica biliaris • Pancreas
|
| Pars inferior |
Intestinum • Intestinum tenue (Duodenum • Ieiunum • Ileum) • Intestinum crassum (Caecum • Colon ascendentem • Colon transversum • Colon descendentem • Colon sigmoideum • Rectum) • Anus
|
yx3VPQ5AGHQmKbDjn
Popular posts from this blog
Tabula multilinguis Rosettana in Museo Britannico ostenditur. Tabula Rosettana, [1] etiam titulo OGIS 90 agnita, est stela decreto de rebus sacris in Aegypto anno 196 a.C.n. lato inscripta. Tabula iuxta Rosettam Aegypti, urbem in delta Nili et ad oram maris Mediterranei iacentem, anno 1799 a milite Francico reperta est. Inventio stelae, linguis duabus scripturisque tribus inscriptae, eruditis Instituti Aegypti statim nuntiata est; ibi enim iussu imperatoris Napoleonis eruditi omnium scientiarum (sub aegide Commissionis Scientiarum et Artium) properaverant cum expeditione Francica. Qua a Britannis mox debellata, tabula Rosettana Londinium missa hodie apud Museum Britannicum iacet. Textus Graecus cito lectus interpretationi textuum Aegyptiorum (in formis hieroglyphica et demotica expressorum) gradatim adiuvit. Denique textum plene interpretatus est Ioannes Franciscus Champollion. Ab opere eruditorum cumulativo coepit hodiernus scripturae hieroglyphicae linguaeque Aegyptiae a...
1
$begingroup$
This is what I mean as document text image: I want to label the texts in image as separate blocks and my model should detect these labels as classes. NOTE: This is how the end result should be like: The labels like Block 1, Block 2, Block 3,.. should be Logo, Title, Date,.. Others, etc. Work done: First approach : I tried to implement this method via Object Detection, it didn't work. It didn't even detect any text. Second approach : Then I tried it using PixelLink. As this model is build for scene text detection, it detected each and every text in the image. But this method can detect multiple lines of text if the threshold values are increased. But I have no idea how do I add labels to the text blocks. PIXEL_CLS_WEIGHT_all_ones = 'PIXEL_CLS_WEIGHT_all_ones' PIXEL_C...
1
$begingroup$
I have this LSTM model model = Sequential() model.add(Masking(mask_value=0, input_shape=(timesteps, features))) model.add(LSTM(100, dropout=0.2, recurrent_dropout=0.2, return_sequences=False)) model.add(Dense(features, activation='softmax')) model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy']) and shapes X_train (21, 11, 5), y_train (21, 5) . Each timestep is represented by 5 features and return_sequences is set to False because I want to predict one 5D array (the next timestep) for each input sequence of 11 timesteps. I get the error ValueError: y_true and y_pred have different number of output (5!=1) If I reshape the data as X_train (21, 11, 5), y_train (21, 1, 5) instead I get the error ValueError: Inva...
